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VTT PUBLICATIONS 307


llpo KulmalaVTT Manufacturing Technology

Thesis for the degree of Doctor of Technology to be presented with due permission for public examination and criticism in Auditorium 1702 at Tampere University of Technology

on May 26th, 1997, at 12 o’clock noon.

TECHNICAL RESEARCH CENTRE OF FINLAND ESPOO 1997

ISBN 951-38-5052-8 ISSN 1235-0621Copyright © Valtion teknillinen tutkimuskeskus (VTT) 1997

JULKAISUA - UTGIVARE - PUBLISHER

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Technical editing Leena Ukskoski

VTT OFFSETPAINO, ESPOO 1997

Kulmala, Ilpo. Advanced design of local ventilation systems. Espoo 1997, Technical Research Centre of Finland, VTT Publications 307. 80 p. + app. Ill p.

UDC 697.9:658.382Keywords ventilation, indoor air, air flow, exhaust systems, gas dynamics

ABSTRACT

Local ventilation is widely used in industry for controlling airborne contaminants. However, the present design practices of local ventilation systems are mainly based on empirical equations and do not take quantitatively into account the various factors affecting the performance of these systems. The aim of this study was to determine the applicability and limitations of more advanced fluid mechanical methods to the design and development of local ventilation systems. The most important factors affecting the performance of local ventilation systems were determined and their effect was studied in a systematic manner. The numerical calculations were made with the FLUENT computer code and they were verified by laboratory experiments, previous measurements or analytical solutions.

The results proved that the numerical calculations can provide a realistic simulation of exhaust openings, effects of ambient air flows and wake regions. The experiences with the low-velocity local supply air showed that these systems can also be modelled fairly well. The results were used to improve the efficiency and thermal comfort of a local ventilation unit and to increase the effective control range of exhaust hoods.

In the simulation of the interaction of a hot buoyant source and local exhaust, the predicted capture efficiencies were clearly higher than those observed experimentally. The deviations between measurements and non- isothermal flow calculations may have partly been caused by the inability to achieve grid independent solutions.

CFD simulations is an advanced and flexible tool for designing and developing local ventilation. The simulations can provide insight into the time- averaged flow field which may assist us in understanding the observed phenomena and to explain experimental results. However, for successful calculations the applicability and limitations of the models must be known.

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PREFACE

This study is based mainly on the work made during the period 1992 - 1995 in the Institute of Energy and Process Engineering at Tampere University of Technology. It was a part of the industrial ventilation (INVENT) technology programme, financed by the Finnish Technology Development Centre (TEKES). The finalizing of this thesis was made possible by financial support from Jenny and Antti Wihuri foundation and from Emil Aaltonen foundation, which is gratefully acknowledged.

I wish to express my gratitude to Professor Antero Aittomaki, my thesis supervisor for his guidance, and to Mr Esko Tahti, leader of the INVENT group, for his encouragement during this work.

I would like to thank my colleagues Mr Arto Saamanen, Mr Seppo Enbom, and Mr Kimmo Heinonen at VTT for fresh research ideas and for coauthoring some of the publications. I thank PhD Hannu Ahlstedt for his help in the numerical simulations and Mr Pentti Saarenrinne for his help in the LDA-measurements.

I would like also to thank Mr Matti Savela and Mr Jarmo Ruusila, members of the laboratory staff in the Energy and Process Engineering Institute, for their help in building the measurement system. To Mr Jouni Uusitalo and Mrs Pirjo Turunen I express thanks for their carefully made measuring work and for a pleasant co-operation.

Most of all I thank my family, Tarja, Juhana and Tessaliina for their loving support during this work.

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LIST OF PUBLICATIONS

This thesis consists of the following papers

1. Kulmala, Ilpo (1993). Numerical Calculation of Air Flow Fields Generated by Exhaust Openings. Ann. Occup. Hyg. 37, pp. 451 - 467.

2. Kulmala, Ilpo and Saarenrinne, Pentti (1995). Numerical calculation of an air flow field near an unflanged circular exhaust opening. Staub - Reinhaltung der Luft 55, pp. 131 -135.

3. Kulmala, Ilpo (1995). Numerical Simulation of Unflanged Rectangular Exhaust Openings. Am. Ind. Hyg. Assoc. J. 56, pp. 1099 - 1106.

4. Kulmala, Ilpo and Saarenrinne, Pentti (1996). Air flow near an unflanged rectangular exhaust opening. Energy and Buildings 24, pp. 133 - 136.

5. Kulmala, Ilpo (1997). Air flow field near a welding exhaust hood. Appl. Occup. Environ. Hyg. 12, pp. 101 - 104.

6. Kulmala, Ilpo (1995). Numerical Simulation of the Capture Efficiency of an Unflanged Rectangular Exhaust Opening in a Coaxial Air Flow. Ann. Occup. Hyg. 39, pp. 21 - 33.

7. Kulmala, Ilpo (1994). Numerical calculation of the capture efficiency of an unflanged circular exhaust opening. In Ventilation '94, Proceedings of the 4th International Symposium on Ventilation for Contaminant Control. Arbete och Halsa 1994:18, pp. 339 - 344.

8. Kulmala, Ilpo (1994). Numerical Simulation of a Local Ventilation Unit. Ann. Occup. Hyg. 38, pp. 337 - 349.

9. Kulmala, I., Saamanen, A. and Enbom, S. (1996). The effect of contaminant source location on worker exposure in the near-wake region. Ann. Occup. Hyg. 40, pp. 511 - 523.

10. Kulmala, I. and Saarenrinne, P. Numerical simulation of a lateral exhaust hood for a hot contaminant source. Prepared for publication.

11. Heinonen, K., Kulmala, I. and Saamanen, A. (1996). Local ventilation for powder handling - Combination of local supply and exhaust air. Am. Ind. Hyg. Assoc. J. 57, pp. 356 - 364.

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CONTENTS

ABSTRACT 3PREFACE 4LIST OF PUBLICATIONS 5

NOMENCLATURE 8

1 INTRODUCTION 101.1 Efficiency of local ventilation 101.2 Objectives of the study 13

2 DESIGN METHODS OF LOCAL VENTILATION SYSTEMS 142.1 Present practice of local ventilation design 14

2.1.1 Guidelines for specific operations 142.1.2 Experimental methods 142.1.3 Capture velocity method 15

2.2 Potential flow solutions 182.3 Computational Fluid Dynamics (CFD) modelling 20

3 SIMULATION METHODS USED IN THE STUDY 233.1 Mean flow equations 233.2 Turbulence modelling 233.3 Boundary conditions 26

4 EXPERIMENTAL FACILITIES AND METHODS 294.1 Experimental setup 294.2 Air velocity measurements 314.3 Tracer gas measurements 324.4 Mass concentration measurements 34

5 SIMULATION AND EXPERIMENTAL RESULTS 355.1 Exhaust openings in still air 35

5.1.1 Two-dimensional openings 385.1.2 Axisymmetric openings 405.1.3 Three-dimensional openings 42

5.2 Effect of ambient air movements on capture efficiency 455.2.1 Exhaust openings in a uniform air flow 455.2.2 Verification of a point sink model 50

5.3 Effect of contaminant source momentum on capture efficiency 555.4 Use of a local supply air 615.5 Wake effects on worker's exposure 67

6

6 CONCLUSIONS 72

REFERENCES 74

PAPERS 1-11

7

NOMENCLATURE

AabCc„ c„ QCp

DDsdEGGbGaGrgIkLPPkQqrTtU,UiU, V, w U0U, V, w

y, za&heyeKXA4MtV

p

area of exhaust opening width of rectangular opening length of rectangular opening concentrationempirical constants in the k-e turbulence modelspecific heat at constant pressurediameter of circular openingdiameter of heat sourceparticle diameterempirical constant in logarithmic lawcontaminant generation ratebuoyancy production of turbulent kinetic energyrate at which contaminant is captured by an exhaust systemrate at which contaminant is escaped into workplace airmagnitude of the acceleration due to gravityturbulence intensityturbulence kinetic energymixing lengthmean pressurestress production of turbulent kinetic energyconvective heat release ratevolumetric flow rateradial coordinatemean temperaturefluctuating temperaturemean velocity component in the direction x,fluctuating velocity component in the direction xtmean velocity components in x, y, z directionsmean velocity at the hood facefluctuating velocity components in x, y, z directionscartesian co-ordinatesthermal diffusivity, \/pcPcoefficient of thermal expansionKronecker delta, 5,y= 1 for i=j and 0 otherwiseturbulence dissipation ratecapture efficiencytangential coordinatevon Karman’s constantthermal conductivitydynamic viscosityturbulent viscositykinematic viscosityfluid density

8

ffk, at, aT turbulent Prandtl number for k, e and T ac turbulent Schmidt number

wall shear stress mean part of dependent variable velocity potential, fluctuating part of dependent variable stream function

9

1 INTRODUCTION

The purpose of an industrial ventilation system is to provide healthy working conditions and an appropriate environment required by the manufacturing processes. The two major types of ventilation systems are general, or dilution, ventilation and local ventilation.

In industry, the dilution ventilation method is usually used to control temperature and humidity. It may also be used to control contaminants if the contaminant generation rate is low and the sources are evenly distributed or mobile (e.g. forklift trucks). Contaminated air is usually exhausted outdoors and large volumes of makeup air are supplied to dilute the contaminant concentration to acceptable levels. However, unless the contaminant generation rates are low, high concentrations are always found near the sources. It is evident that the contaminant concentrations at the breathing zone of any worker in the near vicinity of the contaminant source may not be reduced to a safe level with general ventilation only, and therefore a more efficient control system is needed.

Local ventilation is widely used to bring the concentrations of airborne contaminants to acceptable levels. Local exhaust hoods achieve this control by generating a flow field towards the exhaust opening which removes airborne contaminants close to their point of generation. In this way the airborne contaminants are prevented from entering the workplace air. The drawback of a local exhaust is, however, that its effective control range is very limited. Therefore local exhaust has recently been used in combination with local supply air to protect the workers from exposure at individual work stations by providing clean air and directing contaminants away from the breathing zone. For manual work in particular, local ventilation is often the only possible means to reduce the worker’s breathing zone concentrations to acceptable levels.

Local exhaust ventilation (LEV) can be applied successfully to most processing industries over a wide range of operations. A properly designed ventilation system obtains the maximum efficiency with the minimum exhaust flow rate so that investment and heating costs and power requirements can be kept down. The exhaust air is usually discharged into the outdoor air either directly or through cleaning equipment. With an optimally designed local ventilation system the exhaust concentration is high, thus allowing the economical cleaning of the exhaust air.

1.1 EFFICIENCY OF LOCAL VENTILATION

One measure for exhaust hood performance is capture efficiency. This is defined as the ratio between the rate of contaminants directly captured by

10

the exhaust system Gex to the contaminant generation rate G (Jansson, 1980; Ellenbecker et ah, 1983; Fletcher and Johnson, 1986; Madsen et al., 1993):

The concept of capture efficiency is useful in determining the contaminant removal efficiency. It is often necessary in estimating the rate of contaminants released into the workplace air by processes under the control of LEV systems. This rate is calculated by

Gr = (1 - rj)G (2)

However, the worker’s exposure may not be related directly to the capture efficiency. This is especially the case when local supply air is used together with local exhaust to protect the worker. Another measure for the local ventilation efficiency is therefore its ability to reduce contaminant concentration in the worker’s breathing zone (paper 11).

The efficiency of any local ventilation system depends on the transport of contaminants from their source of origin to the exhaust opening or openings. This can be affected by several factors, the most important of which are shown in Fig. 1 and discussed below.

3. MOMENTUM OF CONTAMINANT SOURCE

1.EXHAUST OPENING AND FLOW RATE

2. AMBIENT AIR CURRENTS

4. AUXILIARY AIR

5. WORKER

EFFICIENCY OF LOCAL VENTILATION SYSTEMS

Figure 1. Factors affecting the efficiency of local ventilation systems.

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1. Exhaust opening and air flow rate. These are the key factors common to all local exhaust ventilation systems. The exhaust air flow through the opening generates an air flow field which removes contaminants from a region close to the point of generation. This flow field is affected by the construction, size, shape and location(s) of exhaust hood(s) relative to the contaminant source and the exhaust air flow rates.

2. Ambient air currents present in industrial halls interact with the velocity field produced by the local ventilation system. This interaction usually reduces the performance of the local ventilation systems. Ambient air currents may be caused by the motion of machinery, draughts from windows and doors, supply air jets, convective flows from hot surfaces, etc.

3. Momentum of contaminant source depends on the convective heat release rate from hot sources, and, in the case of particulate contaminants, on their size, distribution, release velocity and direction.

4. Auxiliary air can be a local low-velocity supply designed primarily to protect the worker or to direct contaminants towards the exhaust hood. Auxiliary air also includes jets used to enhance the capture efficiency of exhaust hoods such as push-pull hoods (Huebner and Hughes, 1985; Robinson and Ingham, 1996) and Aaberg hoods (Germann, 1993).

5. The worker may affect the flow field and thus the efficiency by producing wakes as the air passes around his or her body. The worker’s movements also produce air currents which may affect the exhaust air flow field and the exposure.

The efficiency of any local ventilation system depends on the complex interaction of these factors. Their effects on the performance should be determined accurately in the design of local ventilation systems. However, this is very difficult with the present design practices, which are based on empirical equations or on information about previous ventilation systems for specific industrial operations. A common engineering approach has been to select a conservative exhaust flow rate, which results in overdimensioning and excessive initial and operating costs (Goodfellow, 1985). This is not a good way to design and it is clear that more rigorous design methods are needed. A deeper insight into the physical phenomena and thus more efficient local ventilation solutions can be achieved by solving the fundamental equations describing air and contaminant flows near the contaminant source. Because of the complexity of these equations they must be solved numerically. This has become possible in recent years mainly as a result of the developments in computer technology and computational techniques, and because of the formulation of practically applicable

12

turbulence models. However, so far computational fluid dynamics (CFD) simulations have only rarely been used in local ventilation studies. The application of this method still requires more experience to gain wider acceptance.

1.2 OBJECTIVES OF THE STUDY

The aim of this study was to determine the applicability and limitations of CFD simulations as a design tool for local ventilation systems. In addition, the results were used to examine the possibilities of potential flow models in modelling local exhaust ventilation. This will allow more reliable methods to be developed for predicting the influence of the various factors on contaminant control and worker protection. In one particular case the results of the CFD simulations were used to optimize the efficiency of local ventilation systems for powder handling.

The emphasis of this study was on the application of the existing simulation techniques to modelling local ventilation. The most important factors which influence the efficiency of a local ventilation system were determined and their effect on the performance was studied in a systematic manner. An important step in developing numerical models is to verify the accuracy of the calculated results. Therefore a measurement system was built and extensive tracer gas and air velocity measurements were made under controlled conditions to validate the calculations. Information from this study would be useful in modelling local ventilation, designing efficient local ventilation systems and in improving working conditions in industry.

The thesis consists of eleven papers concerning the simulation of local ventilation and they are reproduced as appendices.

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2 DESIGN METHODS OF LOCAL VENTILATION SYSTEMS

2.1 PRESENT PRACTICE OF LOCAL VENTILATION DESIGN

2.1.1 Guidelines for specific operations

The most straightforward way for designing local ventilation systems is to use information on solutions for specific operations that have been shown to be successful. This is a common design procedure for complex configurations and a large number of these solutions is collected in the American Conference of Governmental Industrial Hygienists (ACGIH) industrial ventilation manual, which contains several design instructions for different industrial processes (ACGIH, 1992). The design guidelines include instructions with drawings for the construction of key elements, recommended flow rates and associated pressure losses. Details about specific control systems are also published in many professional journals, which may provide designers with useful advice and inspiration. Unfortunately, it is rare that one is dealing with an industrial process that is identical to the one for which the ventilation system is already published.

The ACGIH manual provides reasonable assurance that the ventilation system will control the transport of contaminants to the workplace environment. However, the recommended practises do not enable designers to predict contaminant concentrations to ensure that mandatory health standards are met (Heinsohn, 1991). Moreover, the instructions generally deal with exhaust hood designs and flow rates; they do not provide much information on the use of local supply air.

2.1.2 Experimental methods

If no prior knowledge is available for a particular case, full scale model constructions and laboratory experiments can be used to develop an efficient system. These experiments are usually tedious and for reliable results several repetitions are required due to the inherent variations in the measurements. In addition, the results can be applied only to the range of air flow rates and to the geometric configurations for which experimental data is available. However, carefully made measurements under controlled conditions give the most realistic picture of the performance of local ventilation systems. In any case, experiments are often needed to verify the results obtained by other design methods.

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Another way to study local ventilation system experimentally is to use scale models. In scale model studies the dimensions of the actual system are scaled down using a scaling factor which must be the same for all three coordinates. Experiments on scale models have mainly been made for designing exhaust systems for large hot contaminant sources such as pots and furnaces in metallurgical industry (Bender, 1979; Cesta, 1989; Baturin, 1972; Skaret, 1986). The data from the relatively cheap small model can be converted into design information by using scaling laws. This practice calls for a careful obedience to the fundamental similarity laws when studying the actual ventilation problems.

In the study of non-isothermal flows the geometric, kinematic and thermal similarity criteria must be met (Awbi, 1991). To achieve kinematic similarity the Reynolds and Froude numbers of the model and the full scale value must be equal. Moreover, to achieve thermal similarity between the model and the prototype the Peclet numbers must be equal:

' Ux' UxV FS V

pU2 pU2gxAp FS gxAp

Ux Uxa FS a

(3)

(4)

(5)

where U is a reference velocity, x is a characteristic dimension, Ap is density difference, g is the magnitude of the gravitational acceleration and a is the thermal diffusivity. The similarities of the Reynolds number and the Peclet number Pe = RePr imply that the Prandtl number must also be similar. In practice a complete similarity is not possible, and the scaling is done by keeping the Froude number constant because it is the dominant parameter in buoyancy induced flows. This may lead to uncertainty when the low-Reynolds-number model data are used to estimate by extrapolation the desired high-Reynolds-number full-scale data (Skaret, 1986). However, scale models have been successfully used for buoyant flows of practical interest and they are useful also in visualizing the flow patterns.

2.1.3 Capture velocity method

The capture velocity method is widely used when designing relatively simple configurations consisting of an exhaust hood near a contaminant source. Capture or control velocity is defined as the air velocity at any

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point in front of the hood necessary to overcome opposing air currents and to capture the contaminated air by causing it to flow into the exhaust hood (ACGIH, 1992). A slightly different approach to dust control is the null point theory developed by Hemeon (1963). In this method a control velocity must exist, not only at the source, but also at the null point. The null point is defined as the distance from the contaminant source to the point at which the release energy has been expended and the velocity of contaminants has decreased to that of random air currents in the room. Empirical values of the null point velocity have been proposed by Hemeon and they are in the range of 0.2 - 0.5 m/s.

Descriptions of this approach emphasize the need to eliminate or minimize all disturbing air motions about the contaminant source. Such movements are generated by the source itself, or they are created by operations remote from the source, such as moving machinery or spot heating and cooling equipment. Capture velocities are then determined based on the minimum disruptive air flow that can reasonably be attained. The hood is located as close as possible to the source and is shaped to control the area of contaminant release.

For enclosures where contaminants from the process are released inside the hood, the air flow required for contaminant control is simply calculated by multiplying the inward air velocity needed to prevent escape by the area of openings into the enclosure. In most applications, face velocities in the range of 0.5-1 m/s are sufficient (McDermott, 1976; Burgess et al., 1989).

Table 1. Minimum control velocities (ACGIH, 1992; Brandt, 1947).

Condition of Dispersion of Contaminant

Examples of Processes or Operations

Capture velocity, m/s

Released with practically no velocity into a still air

Evaporation from open vessels

0.25 - 0.5

Released at low velocity into moderately still air

Spray booths; welding; plating

0.5 - 1

Released with considerable velocity or into zone of rapid air motion

Spray painting in shallow booths; barrel filling

1 - 2.5

Released at high initial velocity or into zone of very rapid air motion

Grinding; abrasive blasting; surfacing operations on rock

2.5 - 10

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The proper selection of the capture velocity is very important in the successful design of exterior hoods. Too high a velocity will result in good capture efficiency, but the exhaust air flow rate will be excessive, thus leading to high capital and operating costs. On the other hand, if the capture efficiency is too low, it may produce poor performance and high exposure. The values for the necessary capture velocities are empirical and general guidelines for the velocities are given in Table 1. This table was adapted directly from Brandt (1947), and has seen little change in the last 50 years. The range of velocities is large and subjective decisions are required regarding the strength of disturbing cross draughts and the generation rate of the contaminant. More precise capture velocities for some specific operations have been given in the literature (Vogel, 1975).

After choosing the appropriate capture velocity, the required exhaust air flow rate is estimated from the air velocity fields generated by unobstructed exhaust openings. In general, this depends on the distance between the con-

Table 2. Centreline velocities for free-standing exhaust openings. A is the hood face area, a is the width and b the length of a rectangular opening, D is the diameter of a circular opening and U(x) is the velocity along the centreline at a distance x from the inlet plane. U0 is the mean face velocity.

Opening References

Unflangedrectangular

10.93 + 8.58 a2

a = (xl\[A)(blaf

0 = 0.2(x/Va)"1/3

Fletcher (1977)

Flangedrectangular

^ arctanT 2xf4x2 + a2 + b2

Tyaglo and Shepelev (1970)

Unflangedcircular

11+12.73 {x/Df

DallaValle(1952)

Flangedcircular

i- xlDVO.25 + (x/D)2

Drkal (1970)

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taminant source and the exhaust opening and on the hood geometry. To facilitate the design it is necessary to describe the velocity field of the inflowing airstream in a simple manner. Therefore flow rates are usually determined from centreline velocity equations that relate the velocity in front of the hood as a function of the distance between the source and the hood face to the hood geometry being considered. The appropriate centreline velocity formulas for basic types of exhaust openings are presented in Table 2. These equations have been found to describe the centreline velocities well (papers 1, 2, 3 and 4).

The capture velocity method has been questioned for various reasons. It does not take directly into consideration the effect of contaminant source momentum, cross draughts or other air disturbances (George et al., 1990). There are also difficulties when the capture velocity method is applied to large contaminant sources (Conroy and Ellenbecker, 1989). The centreline velocity formulas do not account for sources located off the hood centreline. Current design equations for predicting capture velocity are established on the basis of an unobstructed flow field into the exhaust hood (ACGIH, 1992). There are difficulties also when velocity fields are determined for more complex exhaust openings. The most fundamental deficiency in designing a LEV system with the capture velocity method is that the designer can not predict how effective the design will be in reducing workers’ exposure to airborne contaminants (Heinsohn and Choi, 1986; George et al., 1990).

2.2 POTENTIAL FLOW SOLUTIONS

In recent years, as a step towards a more rigorous design method, potential flow theory has been used to describe the flow near exhaust openings. In this way the flow is idealized by assuming it to be inviscid and irrotational, which greatly simplifies its mathematical treatment. This is possible because viscous effects occur appreciably only along solid surfaces and in the region close to the opening. These viscous boundary layers have little influence on the flow field of unobstructed exhaust openings and can therefore be ignored.

Irrotational, incompressible and frictionless fluid flow can be described using the potential flow theory. In that case there is a scalar velocity potential 4> so that the velocity component Ut in the direction x, is

u, . f* (6)

Substituting the conditions imposed by continuity gives Laplace’s equation

18

_d_(ty = o dxi dxi

(7)

This equation, taken in conjunction with appropriate boundary conditions, can be solved numerically or in some cases analytically to give the ideal flow field.

When calculating the velocity potential at a point near an infinitely flanged exhaust opening, the hood face can be assumed to be divided into many area sinks, each of them contributing to the to the potential at a point in space. The overall velocity potential is then obtained by integrating over the inlet area. The velocity component in the ^-direction, for example, is then

i Lx. ]dA (8)a dx 2irAr

where q is the exhaust flow rate, A is the area of the exhaust opening and r the distance between a point in space, where the velocity is calculated, and the elemental area dA at the exhaust opening. This integral for an infinitely flanged rectangular opening was first solved in closed form by Tyaglo and Shepelev (1970). The model was later validated by Flynn and Fitzgerald (1989). A potential flow model for an infinitely flanged circular opening was derived by Drkal (1970), and a model with empirical modifications by Flynn and Ellenbecker (1985). It is also possible to determine the velocities for arbitrarily shaped flanged openings by numerical integration (Alenins and Jansson, 1989). A good agreement of the theoretical models with the experimental data indicates that the potential flow approximation applies to the flow into unobstructed exhaust hoods.

For an arbitrarily shaped configuration there is no analytical solution. When the potential functions of the flow field are unknown, numerical methods may be used to obtain the solution of the flow field. Flow fields have been modelled using the finite difference method (Anastas and Hughes, 1989; Anastas, 1991; Flynn and Miller, 1988), the finite element method (Garrison and Wang, 1987, Garrison and Park, 1989) and by the boundary integral method (Flynn and Miller, 1989).

Potential flow solutions are useful to illustrate the effect of cross-draughts on the efficiency of local exhaust hoods. In this way an idealized uniform velocity field is superpositioned on the flow field of the exhaust opening. This is possible because Laplace’s equation is a linear homogeneous differential equation. If a flow field is known to be the sum of two separate flow fields, one can combine the harmonic functions for each to describe the combined flow field. However, analytical solutions are only available for

19

flanged circular and rectangular openings. In this study a simple model is presented where an unflanged exhaust opening is modelled as a point source.

Potential flow has also been used to model the combination of exhaust and jet-induced flows which are created by exhaust hoods reinforced by jets (Hunt and Ingham, 1993; Hunt and Ingham, 1996). In these cases the flow field was divided into two regions. In the jet region the turbulent flow was solved separately, while the other part of the flow was assumed to be inviscid and was calculated numerically by solving the Laplace's equation. Good agreement between the theory and experiments was reported.

Empirical equations have been used to describe the contaminant dispersion around streamlines (Flynn and Ellenbecker, 1986; Conroy and Ellenbecker, 1989). The particle trajectories, and thus the efficiency of local exhaust systems, can also be calculated with reasonable accuracy if the particle generation does not affect the exhaust flow field (Alenins and Jansson, 1989). On the other hand, with unflanged openings the boundary conditions are difficult to determine accurately. Moreover, the analytical solutions are restricted to unobstructed exhaust openings. The greatest limitation of these models is that they do not perform well in flows or flow regions where the turbulent stresses affecting the flow are significant. Such important flows are, for example, wakes caused by obstacles in the flow field and buoyant flows.

2.3 COMPUTATIONAL FLUID DYNAMICS (CFD)MODELLING

The transport of contaminants and the efficiency of local ventilation depend on the air movements near the contaminant source and the exhaust hood. Therefore an optimal design of local ventilation systems needs a proper prediction of the air flow field near the contaminant source and the exhaust hood. The turbulent air flow field can in principle be determined by solving the exact time-dependent equations describing fluid flow directly. However, turbulent flow contains motions which are much smaller than the extent of the flow domain and, as the Reynolds number increases, the ratio of the large scales to small length scales increases. In order to resolve the small scale motion in a numerical procedure, the mesh cells would have to be extremely small for flows of any practical importance. Storing and solving the flow variables at so many grid points is still beyond the capacity of present computers. On the other hand, although the influence of turbulence fluctuations on the mean flow may be of great importance, interest is mainly on the mean flow quantities. For this reason, turbulent flow is normally analyzed using statistical methods. The instantaneous values of variables are divided into mean and fluctuating parts, and a suitable turbu

20

lence model is used to describe the momentum and scalar transport in the flow.

In numerical simulations the calculation domain is divided into a number of grid points, and the differential equations are converted into a system of algebraic equations by discretization. A common discretization procedure in CFD is the finite volume method. The algebraic equations are solved iteratively for each variable at discrete spatial grid points. The accuracy of the simulations depends largely on the applicability of the turbulence model used in the simulations, the accuracy of the numerical techniques and on the reliability of the boundary conditions. Moreover, the calculation domain should be discretized with a fine enough grid to obtain grid independent solutions.

During the past two decades there have been many studies on modelling turbulent air flows in ventilated spaces by numerical methods. However, much less research has been done on the viability of CFD for modelling flows in local ventilation applications. These simulations have mainly dealt with jet augmented ventilation systems, the flows around worker in a uniform flow and exhaust openings.

Heinsohn and Choi (1986) predicted two-dimensional turbulent velocity and contaminant concentration fields for a push-pull ventilation system in a pioneering work simulating local ventilation. They developed their own code for calculating the turbulent flow field using the k-e turbulence model. Flynn et al. (1995) made three-dimensional finite element simulation of a push-pull ventilation system with a one-equation turbulence model. Comparison with experiments showed reasonable agreement with predicted and measured velocities and jet trajectories, whereas turbulent kinetic energy showed less consistent agreement. Recently, Robinson and Ingham (1996) modelled the push-pull ventilation system and introduced a variety of approximations to reduce the computational time required. They compared the results with previous experimental work and demonstrated good agreement with simulations. Ingham (1994) solved the air flow field of an Aaberg exhaust system, which uses a jet to improve the capture efficiency of a slot hood. He found good agreement between a mathematical model, numerically calculated velocities, and experimentally observed velocities.

Braconnier et al. (1991) studied numerically the effects of cross-draft on the capture efficiency for an exhaust system of a surface treatment tank, and the results were verified by velocity and tracer gas measurements. Scholer (1993) studied the effect of flanges and streamlining of the inlet opening on the velocities generated by a flanged circular hood.

In addition to the calculation of local exhaust ventilation, calculations have been made to study the worker's presence on the local air movements. Flynn

21

and Miller (1991) determined the flow field around the worker by solving numerically the unsteady Navier-Stokes equations using the discrete vortex method. Ingham and Yuan (1992) determined the flow past the worker into a line sink in a wall with the boundary element method. Recently Dunnett (1994) predicted the time-dependent flow field using the k-e turbulence model and artificial small perturbations to start the shedding process around the worker. Recently, Flynn et al. (1995) used a particle trajectory method to predict the worker's exposure assuming a two-dimensional flow. In all these studies a two-dimensional flow was assumed and the worker was modelled as an ellipse.

Full-scale experiments may be the most realistic design method for local ventilation. In comparison, CFD simulations provide several advantages over these experiments. They make it possible to study installations in the development stage and they also offer the opportunity of studying the influence of particular factors isolated from all other factors. Thus the simulations allow reliable estimation of various trends. CFD simulations provide also detailed information on mean air flow, temperature and concentration fields and may permit a more precise understanding of the flow processes. The previous studies have proved their usefulness in local ventilation applications. However, more experience in the use of CFD is needed to make it more attractive to ventilation engineers at large.

22

3 SIMULATION METHODS USED IN THE STUDY

3.1 MEAN FLOW EQUATIONS

The mean air velocity and contaminant distribution in local ventilation applications can, in general, be determined by solving the flow equations describing the conservation of mass, momentum, thermal energy and species concentration. Assuming steady flow and neglecting density fluctuations these time-averaged equations can be expressed in tensor notation as:

Continuity

(9)

Momentum

d (10)

Thermal energy and species concentration conservation

do

where Ut is the mean and ut the fluctuating velocity component in the direction Xj, P is the mean pressure, n is the dynamic viscosity and is the turbulent Prandtl or Schmidt number. is the source term for the dependent variable <f> which may stand for either the species concentration C or for the temperature T. The air density p is calculated by the ideal gas law. The correlations of fluctuating quantities putUj and pw,<£ in equations (10) and (11) represent the transport of momentum and heat or mass due to the turbulent motion. These turbulent fluxes must be related to known or calculable quantities before the equations can be solved.

3.2 TURBULENCE MODELLING

In this work the calculations were made mainly using the common high- Reynolds number k-e turbulence model (Launder and Spalding, 1974). In one case the calculations were made using also the algebraic stress model (ASM) and the details of this method are given in paper 2.

The k-e model relates the turbulent stresses and fluxes to the mean gradients of dependent variables through an eddy viscosity

23

(12)dui dUj

dXj dxj

= (13)fa,

where ot is assumed to be a constant and the eddy viscosity /xT is calculated by

pUUj = -byp -pT

(14)

in which k is the turbulent kinetic energy and e is its isotropic dissipation rate. The values of k and e required in Equation (14) are obtained by the solution of modelled transport equations for k

- i o. * a,, ox:+ Pk + Gb ~ Pe (15)

and e

dx;(p^e) _d_

8X;(c * ^r)|i

O OX:+ C.^P.-G.) - C,p.L <16)

where

♦ M (17)

represents the shear production of turbulence kinetic energy by the interaction of mean velocity gradients and turbulent stresses and

Gb = oT oxj(18)

is the generation of turbulence due to buoyancy. The commonly used values for the empirical constants appearing in the above equations are listed in Table 3 (Launder and Spalding, 1974).

24

Table 3. Values of the constants in the k-e model.

C„ c, c2 0"c <?c aT

0.09 1.44 1.92 1.0 1.3 0.7 0.7

The values of the empirical constants CM, C, and C2 in Table 3 have been determined from basic types of flows such as local-equilibrium shear layers near wall and grid turbulence. The diffusion constants ok and at are assumed to be close to unity. Final tuning of these constants was made by computer optimization (Launder and Spalding, 1974). In a fully turbulent flows the values of the turbulent Schmidt and Prandtl numbers vary somewhat across the flow region but usually they are assumed to be constant and near unity (Reynolds, 1974). The values for oc and <xT in Table 3 are the default values of the FLUENT code (FLUENT, 1995).

The above constants have been found appropriate to a variety of turbulent flows. However, they are not universal and it has been discovered that they do not produce good agreement with data for the axisymmetric jet or weak shear flows. To improve these predictions modifications for the constants Cp and C2 in 3 have been have been proposed (Rodi, 1984; Launder and Spalding, 1974).

The k-e model is currently perhaps the most commonly used turbulence model and it has been applied successfully to a wide range of flow predictions. However, it is based on the assumption that the eddy viscosity is the same for all Reynolds stresses and heat or concentration fluxes (isotropic eddy viscosity). This lack of direction dependence implies that the k-e model can not be expected to work well for strongly anisotropic flows, such as flows with strong streamline curvature or strongly buoyant flows. For such flows second order turbulence closures, such as the Reynolds stress models (RSM) in which all the stresses are calculated from their own transport equations or the algebraic stress model (ASM), may perform better. In the latter method modelled transport equations for the Reynolds stresses and heat fluxes are simplified to yield algebraic equations. However, the use of second order closures greatly complicates the task of numerical solution compared with the k-e model.

A further level of sophistication in turbulence modelling is Large Eddy Simulation (LES). In turbulent flows, large scale structures absorb energy from the mean flow and they tend to be highly anisotropic and vorticical in nature, whereas the small eddies are more nearly isotropic and universal. In LES the large-scale motion of the turbulent flow is computed directly from the flow equations, and only the small-scale motion is modelled with scales less than the numerical grid (Wilcox, 1993). The LES is considered to be a potentially promising and universal method, but so far the very

25

large computational resource requirements have limited its application to research topics.

In this study the time-averaged conservation equations with turbulence energy and dissipation rate were solved with the FLUENT version 3.02 or 4.32 computer codes based on the finite volume method. The calculations were performed on a Sun Sparc Server 690 MP or on a Digital Alpha Station 600 5/333. The solution algorithm was a semi-implicit method for pressure linked equations (SIMPLE), and the QUICK or power-law differencing scheme was used for the discretization of the convection terms (Leonard, 1976; Patankar, 1980).

3.3 BOUNDARY CONDITIONS

The accuracy of the simulations is very dependent on the accuracy of boundary conditions. The main types of boundaries usually encountered in local ventilation applications are wall and free boundaries, exhaust and supply air openings, and symmetry boundaries.

To avoid overly high grid densities near the surfaces, wall functions were employed. In this method the logarithmic law of the wall relation for velocity is used to patch the region of flow lying between the wall and the first calculation point adjacent to the wall (Launder and Spalding, 1974):

(19)

where

(20)

tw is the shear stress on the wall, k is the von Karman's constant, E is a roughness parameter and yP is the distance of the first calculation point from the wall. The boundary condition for the dissipation rate eP is (Rodi, 1984)

The near wall value for kP was computed by solving the complete transport equation for k in the near wall control volume, with the wall shear stress included in the production term and a zero normal gradient assumed for k at the wall (FLUENT, 1995).

In local ventilation simulations the region of interest includes the exhaust

26

opening, the contaminant source, and possibly the worker and local supply air openings. The calculation domain is often restricted by free-stream boundaries at which the dependent values, such as the velocity components and turbulence quantities, are unknown. They are also very difficult to determine accurately. To circumvent the need to determine these variables, a fixed boundary condition was used and the inlet turbulence and dissipation were set to a small value at the free-stream boundaries. This method can be used if the boundaries are sufficiently far from the supply and exhaust openings, and from buoyancy sources so that the velocities at the boundaries are relatively small. The fixed pressure boundary condition allows the user to input die total pressure at a boundary instead of defining the flow velocity. FLUENT (1995) can then compute the normal velocity component and the static pressure at the boundary by applying Bernoulli’s equation. This may lead to errors in the velocities, if the boundaries are too close to the exhaust or supply air openings. However, it has been found in several studies (papers 1-8,10 and 11) that if the free-stream boundaries are far enough from the openings, the velocities at the boundaries are small and the calculated velocities near the exhaust opening are fairly accurate.

At free-stream boundaries the flow direction may not be known beforehand. When the fixed pressure condition is applied, and the flow exits through the boundary, all scalar boundary conditions, except the pressure defined for the pressure inlet boundary, are ignored. Scalar properties instead, such as temperature and turbulence variables, are assumed to be equal to the values in the live cell immediately upstream of the exit (FLUENT, 1995).

Supply air outlets and exhaust openings were modelled using velocity boundary conditions. It is also possible to model the exhaust openings using pressure boundaries at the exit, but by using uniform velocity profiles the exact exhaust flow rates can be determined more conveniently. Exit values for scalars at the exit are not necessary, because the Reynolds number at the exit is usually large, and significant influences travel only from upstream to downstream.

The physical parameters at the supply outlet depend on the specific case and they are usually known, or may be calculated, from other quantities. It is necessary to specify the velocity components, fluid temperature, species concentration and the turbulence quantities at the outlet. They were assumed as uniformly distributed across the supply. At the outlet the turbulence was assumed to be isotropic, which is a reasonable assumption for most practical cases (Awbi, 1991), so that the turbulence kinetic energy was calculated by

27

(22)

where / is the turbulent intensity defined as rrns of velocity fluctuation divided by the mean velocity. The exit value of e0 was estimated from a length scale assumption (FLUENT, 1995)

eo3/4, 3/2

■o (23)

where the mixing length lm was calculated by

L = 0.07L (24)

and L is the hydraulic radius of the inlet. The value of 0.07 is derived roughly from the mixing length distribution in turbulent pipe flow (Launder and Spalding, 1972). In practice, turbulence kinetic energy and its dissipation rate within the calculation domain are mainly governed by the local conditions, and the inflow dissipation rates have little effect on the final results (Awbi, 1991).

In the simulations symmetry conditions were used to reduce the size of the calculation grid. At the symmetry plane the normal velocity component and the normal derivatives of all other variables are zero.

28

4 EXPERIMENTAL FACILITIES AND METHODS

An important step in developing numerical models is to verily the accuracy of the calculated results. This calls for extensive laboratory measurements to be conducted under carefully controlled conditions.

4.1 EXPERIMENTAL SETUP

Experiments were made both at Tampere University of Technology (TUT) and at VTT Manufacturing Technology. The local ventilation studies were made in a test room situated in a large laboratory hall at TUT, while the worker exposure measurements caused by wake effects were made in a wind-tunnel at VTT.

The test room (floor area 4.8 m x 3.6 m, height 3.6 m) ventilation system consisted of the general mechanical supply and exhaust, and of local supply and exhaust air (Figure 2). The supply and exhaust fans were driven with frequency controllers and the air flow rates were measured by using standard ISA 1932 nozzles (ISO 5167-1, 1991). The maximum air flow rate was 0.4 m3/s, corresponding to an air exchange rate of 23 h"1, so that steady state situations could be obtained within a reasonable time.

GENERALEXHAUST

LOCALSUPPLY

3.6 mLOCALEXHAUSTLOCAL VENTILATION

UNITGENERALSUPPLY

HEPA-FILTER

4.8 m

Figure 2. Test room ventilation system.

29

The general and local exhaust air flows were exhausted outdoors so that the background tracer gas concentration in the laboratory hall was below the detection limit. The supply air was HEPA-filtered to minimize the influence of background dust concentrations on the results in the experiments made with the flour additive powder (paper 11).

During the measurements the general ventilation supply air was normally introduced through three ceiling-mounted, low-velocity outlets (Halton LVA 200) with dimensions of 0.54 m in length and 1.14 m in width each. When the supply air was from these low-velocity supplies, fairly low velocities inside the test room (below 0.1 m/s) could be obtained even with high air exchange rates. In the experiments which measured the effect of uniform air flow on the capture efficiency of exhaust hoods, the supply air was through a wall-mounted low-velocity diffuser (Halton LVA 250) with dimensions of 0.68 m in length and 1.2 m in width. The velocity distribution of this air terminal unit was made uniform by installing a fabric felt filter downstream of the perforated panel. The general extraction was by a 0.6 m wide and 0.2 m high rectangular grille in the wall at ceiling level (Halton TS-HV 600 x 200). The local exhaust was through a 200 mm diameter duct. In the experiments the duct was connected to different kinds of exhaust openings or to a local ventilation unit (Halton Comfo LCI 1000).

A measuring system was constructed to measure air velocities, temperatures or tracer gas concentrations (Figure 3). The system consisted of a personal computer, a FTIR-analyser (Bomem 100), air velocity transducers (Dantec 54N50 or TSI Model 8470), a datalogger (HP 3497A), a stepping

SAMPLE TUBESSTEPPINGMOTOR

FTIR-ANALYSER BOMEM 100

PERSONALCOMPUTER

MULTICHANNELSELECTOR

DATAACQUISITION HP 3497A

STEPPINGMOTORCONTROLLER

AIR VELOCITY AND TEMPERATURE TRANSDUCERS

Figure 3. Principle of the measuring system.

30

motor and a stepping motor controller, and a multichannel selector. The personal computer was used to control the measuring system and to store the measurement data. The stepping motor was used to move transducers or the tracer gas release point in one direction. Special software was designed and programmed to control the measuring system so that measurements could be made automatically without the need of access to the test room during the measurements.

4.2 AIR VELOCITY MEASUREMENTS

Air velocities were measured with different methods. Laser doppler anemometry (LDA) was used to measure the detailed air velocity near exhaust openings and above a heat source. Hot sphere anemometers were used to measure the air velocities near the local ventilation unit (Comfo LCI 1000). An omni-directional air-velocity transducer (TSI Model 8470) was used to measure fairly low velocities (below 0.5 m/s). Because of its large time constant the transducer was not suitable for measuring turbulence, and therefore turbulence intensity was measured by a low velocity flow analyser (Dantec 54N50).

The advantage of LDA measurements over other air velocity measurements is that there is no solid sensing element in the flow which would disturb the air flow. The velocities were measured by a one-dimensional fiber optical set-up and a PDA processor (manufacturer DANTEC Meas. Tech.). The set-up includes a 3W Spectra Physics 164 Ar-Ion laser. The main optical parameters were: focal length of the front lens 400 mm, beam separation 38 mm, wavelength of light 514.5 nm. The measures of the measurement volume were: diameter 210 /mi, length 4.4 mm, fringes separation 5.4 fim. The probe was mounted on a computer controlled traversing system, which allowed measurements to be made automatically over a predetermined grid.

During the LDA-measurements the flow field was artificially seeded with olive oil droplets by using a TSI Six Jet atomizer (manufactured by TSI Inc., Min, USA) for particle generation. The seeding generator was placed far away from the exhaust opening, just downstream of the low-velocity outlet of the supply air to ensure uniform seeding inside the whole room. The mean diameter of the olive oil particles was 0.6 /mi, according to the manufacturer’s information, so that the particles tracked the flow accurately but were still large enough to scatter sufficient light for the proper operation of the photodetector and the signal processor. The number of samples depended on the measured flow. Typically 3 000 samples were collected in each measuring point when unobstructed exhaust openings were measured under isothermal conditions, whereas in the buoyant flow measurements 24 000 samples were collected in regions of high turbulence.

31

When studying the local ventilation unit the air velocities were measured with the hot-film transducers. The transducer velocity readings were recorded for three minutes in each measurement point and the results were used to calculate mean velocities and turbulence intensities. Sampling times were based on experimental results made in ventilated spaces. Shorter sampling times may not give accurate results for the mean velocities. On the other hand, longer measuring period times do not significantly affect the mean velocities (Thorshauge, 1982). Three minute sampling times correspond also to the recommendations given in a standard for measuring thermal environments (ISO 7721, 1985). The measured velocities and turbulence intensities were then used for the estimation of draft risks.

4.3 TRACER GAS MEASUREMENTS

Tracer gas measurements were made to study the capture efficiency of exhaust hoods, to investigate the supply air distribution near the local supply air unit and to determine the contaminant transport into the breathing zone in the wake region of the mannequin.

The tracer gas used was sulphur hexafluoride (SF6) and its release flow rate was kept constant by a mass flow controller (Bronkhorst type F201 C). In order to obtain a known release rate accurately the mass flow controller was calibrated with a soap bubble calibrator (Gilibrator). The tracer gas concentration was measured in the general and local exhaust ducts by the FTIR-analyser. The sampling distance was located about 25 duct diameters downstream of the inlet openings, and in the duct configuration there were both in the general and local exhaust two 90° elbows. The tracer gas was thus uniformly dispersed across the duct section (Hampl et al., 1986). The release flow rate varied between 0.4 and 2 cm3/s depending on the exhaust air flow rates. The measured concentrations were typically in the range 0 - 12 ppm.

In order to check out the accuracy of the measurement system, tracer gas was released at different flow rates into the exhaust hood and its concentration CM was measured in the exhaust duct downstream of the hood. The calculated concentration Cc was obtained by

Cc = SL (25)q

where G is the tracer gas release flow rate and q the measured exhaust flow rate. This calculated concentration includes the uncertainties due to air flow measurements, the mass flow controller and sampling errors. The calculated and measured concentrations are plotted in Fig 4. Least square fitting to the data points gives

32

(26)

with coefficient of determination R2=0.9991. This good agreement confirms the accuracy of the whole measurement system. Owing to the constant rate of release of the tracer gas and the carefully controlled testing conditions, any variations caused by the measurement system itself could be minimized.

C* = 0.989 Q,

CALCULATED CONCENTRATION Cc (PPM)

o Measurement 1 □ Measurement 2

----- Curve fit

Figure 4. Comparison of calculated and measured concentrations.

Tracer gas measurements were also used to investigate the worker’s exposure in the near wake region caused by a recirculating air flow. These experiments were made at VTT Manufacturing Technology using an open- ended tunnel which was 2 m wide, 2 m high and 4.2 m long. During the measurements tracer gas was released at several points downstream a mannequin installed in the tunnel and its concentration was measured in the breathing zone. A more detailed description of these measurements is in paper 9.

33

4.4 MASS CONCENTRATION MEASUREMENTS

The test room was also used to study the efficiency of various local ventilation systems during manual powder weighing. In these experiments the worker's dust exposure was determined by standard gravimetric filter sampling and by real-time monitoring. The dust sampling filter cassettes were attached to the worker's left lapel. Depending on the filter load, samples were collected on either open-faced polycarbonate (Nuclepore 0.4 pm pore size) or cellulose ester (Millipore 0.8 pm pore size) 37 mm filters. Cellulose ester filters were used when the breathing zone dust concentrations were high. With lower concentrations polycarbonate filters were used because of their better weight stability. To collect measurable quantities of dust within a reasonable time, the sampling was done at 19 1pm. This is between the ventilation rate of a resting person (11.6 1pm) and of a person with light excercise (32.2 lpm) (Heinsohn, 1991). After 24 h of desiccation, both the samples and three blank filters were weighed using a electrobalance with a readability of 10 pg.

Real-time dust monitoring used a portable aerosol photometer (Miniram model PDM-3) attached to the worker's right lapel. The photometer's analog output was recorded at one second intervals with a data logger connected to a personal computer for data analysis.

34

5 SIMULATION AND EXPERIMENTAL RESULTS

5.1 EXHAUST OPENINGS IN STILL AIR

Exhaust devices are the key elements in any local exhaust ventilation systems. Therefore their accurate modelling is essential for reliable predictions of these systems. In this study the air flow fields generated by several unobstructed exhaust openings were calculated and the accuracy of the results was determined by comparing the predicted results with potential flow solutions, LDA measurements or previous experimental results found in the literature. The calculated cases with typical calculation grids are summarized in Table 4.

Table 4. The calculated cases and validation methods.

Case Calculationgrid

Validation References

Unflanged slot 62x37 Potential flow solution

Anastas and Hughes (1989), paper 1

Flanged slot 62x37 Potential flow solution

Drkal (1971), paper 1

Unflanged circular opening

70x58 Experiments,LDA-measure-ments

Dalla Valle (1952), paper 2

Flanged circular opening

78x50 Potential flow solution

Drkal (1970), paper 1

Unflangedrectangularopening

57x25x35 Experiments,LDA-measure-ments

Dalla Valle (1952), papers 1,3 and 4

Flanged rectangular opening

36x24x29 Potential flow solution

Tyaglo and Shepe- lev (1970), paper 1

Misotek hood 36x26x29 LDA-measure-ments

Paper 5

The circular openings were solved in cylindrical co-ordinates, the slots in two-dimensional and the rectangular openings in three-dimensional Cartesian co-ordinates. The co-ordinate systems and computational domains for unflanged openings are shown in Fig. 5. The dimensions in the figure are inside widths or diameters of the exhaust ducts.

35

1 11a

yI [..............

a -To * VI a—1 0 22a 0T0 x 4D 8D

Two-dimensional slot Circular opening

2a

1 j z

y^-i l t6a

0 y 6a J 0 x 6a

Three-dimensional rectangular opening

. 0 12a

Figure 5. Typical computational domains for unflanged openings.

In each case, the hood face was situated in the middle of the computational domain. In the two-dimensional case the air flow field was assumed symmetrical with respect to the x axis. In the three-dimensional case xy and xz planes were planes of symmetry, so that only a quarter of the domain was modelled. Axial symmetry was assumed for the circular openings. The exhaust duct walls were parallel to the symmetry axes.

The calculations and experiments were made for openings with one size and exhaust flow rate only. These kinds of exhaust hoods are typically operated at exhaust velocities which correspond to the Reynolds number in the range of 104 < XJ,p/v < 105 so that the flow is fully turbulent. The turbulent stresses are significant only near duct walls and the flow into exhaust hoods outside the shear layer can be described well as an inviscid, irrotational potential flow. Therefore the results can be applied to other openings with similar geometry as well.

The velocity distribution in the exhaust duct was assumed uniform and parallel to the exhaust duct walls at the boundary. In this way the correct exhaust air flow was obtained conveniently. In reality, the flow would develop along the duct and the velocity would not be constant, but because the partial differential equations describing the flow inside the duct are parabolic, significant influences travel only from upstream to downstream.

36

The conditions at the exhaust opening are therefore very little affected by the downstream conditions.

A fixed pressure boundary condition was used at the free-stream boundaries. This may not be quite valid if the ffeestream boundaries are close to the exhaust opening. Therefore the effect of free-stream boundary locations on the simulations was studied by using different sizes of calculation domains. It was found that an appropriate distance between the exhaust opening and the freestream boundary is about 4A1'2 where A is the face area of the exhaust opening (paper 3). This corresponds to velocities at the boundaries which are less than 1 % of the mean face velocity.

The effect of the grid size on the accuracy of the simulations was studied by calculating the air flow fields with different grid densities. The grids were non-uniform with fine grid spacing near the hood face. Table 5 shows the number of grid points in symmetry planes covering the exhaust opening. These grids were found to produce grid-independent solutions for the flow field near the exhaust opening.

Table 5. Number of grid points across the exhaust opening.

Opening Number of grid points

Reference

2D slot 7 paper 1

Axially symmetric 12 paper 2

Rectangularaspect ratio 1:1 7x7 paper 3aspect ratio 4:3 8x7aspect ratio 2:1 8x6aspect ratio 3:1 10x6

The results can also be used to examine the applicability of line sink and point sink models in predicting air flow into real openings. These simple potential flow models are attractive because they are very easy to use and they give the velocity at arbitrary points in front of an inlet and not at points just along the centreline. Moreover, in the simulations it may be sometimes necessary to give velocities at the freestream boundaries instead of pressure. Velocities induced by point or line sinks can then be used to estimate these velocities at freestream boundaries (Robinson and Ingham, 1996). The potentials of the simple openings can also be easily combined with an ideal uniform flow field to determine the effectiveness of the exhaust opening under ambient disturbances.

37

The velocity induced by a line sink is given in cylindrical co-ordinates by

(27)

where q’ is the exhaust flow rate per unit length, r is the radius and k is a constant which has a value 2 for a line sink withdrawing air from the whole space and 1 for a flanged slot. The velocity of point sink is in spherical co-ordinates

(28)kirs2

where k is 4 for a plane sink and 2 for a flanged sink, and s is the radius. Both the line and point sink have singular points at the origin, where velocities approach infinity so that the results near the origin are not physically meaningful. However, at distances of practical importance this simple model may describe the flow field adequately.

5.1.1 Two-dimensional openings

Slots can be thought of as rectangular unflanged hoods with very large aspect ratio (the ratio of slot length b, to its width, a). Anastas and Hughes (1989) have shown that rectangular exhaust openings behave like slots when the aspect ratio is greater than 100. Slots are an important class of exhaust opening and they are typically used as rim exhaust at large tanks

5—Analytical solution——Numerical solution -•-Line sink

4□

12 3 4

Distance (x/a)

Figure 6. Velocity contours for the upper half of a plain slot by analytical, numerical and line sink solutions (paper 1).

38

or welding exhaust hoods in high velocity low volume local ventilation systems.

Figure 6 shows the numerically and analytically calculated velocity contours together with the line sink model for the plain slot. The velocities are presented as a fraction of the average velocity in the channel (average face velocity). The analytical solutions are obtained by conformal transformation (Streeter, 1948) using an iterative technique presented by Anastas and Hughes (1989).

The agreement between the numerical and the analytical velocity contours is satisfactory. It can be seen that compared to the analytical solution the numerically calculated contours are displaced somewhat in the positive x direction, while the line sink contours are displaced in the negative x direction. The reach in the y direction is also somewhat underestimated by the line sink. The simple line sink model overestimates the centre-line velocities close to the opening (x/a <0.24) and underestimates them further from the opening. In the range 0.5 <x/a < 4 the line sink model underestimates the velocities calculated by the analytical model on the average by 15 %. On the contrary, the numerical calculations overestimate the centreline velocities in the same range by 12 %. Both models tend to be more accurate as the distance from the opening increases.

The analytical solution for an infinitely flanged slot can be obtained by assuming that the inlet is composed of elemental point sinks (Drkal, 1971). The applicability of this model was verified by Anastas and Hughes (1989), who compared theoretical to experimental centre-line velocities and found close agreement.

-r7rrrrr-rx□ -i 1 Distance (x/a)

Analytical solution Numerical solution Line sink

Figure 7. Predicted and theoretical velocity contours for a flanged slot (paper 1).

39

The correspondence between the numerically calculated velocity contours and the analytical model is good, as can be seen in Fig. 7. The line sink model gives velocities which are almost identical to the velocities given by the analytical model further from the opening, where the velocities are less than 20 % of the mean face velocity.

The centre-line velocity of infinitely flanged slot is calculated from (paper 1)

U_ 2— arctan tr

(29)

It is interesting to note that when x/a is large the centre-line velocity in equation (29) can be approximated by the first term in the MacLaurin series expansion

U_UQ

aXTT

(30)

which is the same as obtained by the simple line sink model.

The numerically calculated centre-line velocities are in excellent agreement with the analytical model. The numerical model slightly overestimates the analytically calculated centre-line velocity, but the difference is less than 5 % in the range 0<x/a<4. The line sink model overestimates the velocities near the opening but the difference decreases with increasing distance. In the range 1 <x/a<4 the mean difference between the analytical and the line sink models is only 2%.

5.1.2 Axisymmetric openings

An analytical solution has not been found for an unflanged circular hood. The calculated air velocity contours for unflanged circular openings were thus compared to LDA measurements, Dalla Valle’s experiments and to the simple point sink model, and they are shown in Fig. 8. Where the velocities are in the range from 10 to 50 % of the average face velocity, the k-e model predicts somewhat higher velocities than the measurements, but the overall agreement is fairly good. The velocities were calculated also using the algebraic stress turbulence model (ASM), which gave excellent agreement with the LDA measurements.

The point sink in Fig. 8 is located at the centre of the circular exhaust opening and it is exhausting at the same flow rate as the circular hood. Close to the origin the velocity of the point sink approaches infinity and

40

deviates considerably from the actual fluid velocities. However, at distances greater than about half the duct diameter from the origin, the velocities given by the sink model may be reasonable approximations of the true values in practical applications.

The comparison of the predicted and the measured centre-line velocities shows that the k-e model overestimates the velocities on an average by 6 %, whereas the ASM overpredicts them by 2 % which is close to the uncertainty of the exhaust air flow measurement (ISO 5167, 1991). The Dalla Valle’s empirical equation (Table 2) overestimates the measured centre-line velocities on an average by 8 % when x/D<0.35, and underestimates them by 7% in the range 0.35<x/D<2. The point sink model seems to underestimate the velocities by 20 % in the range 0.5 <x/D <2.

Figure 8. Predicted and measured constant velocity contours for unflanged circular opening (paper 2). The velocities shown in the upper half of the figure were calculated with the ASM and in the lower half with the k-e model.

41

The calculated air flow fields for the flanged circular opening were compared to the solution presented by Drkal (1970) and later validated also by Flynn and Miller (1988). As seen in Fig. 9 there is a good agreement between the analytical and numerical values (paper 1). The point sink model for the flanged hood again overestimates the velocities close to the opening but, when the distance increases, the difference gets smaller. For velocities less than about 20 % of the face velocity the point sink velocities are moderately close to the actual velocities (Fig. 9). The average centreline velocity difference between the point sink model and the analytical model is 16 % in the range 0.5<x/D<2, but it decreases asymptotically as x/D increases.

1 .5— Analytical solution— Numerical solution

■ ■■ Point sink

moca0.5h

0.8 0.4 \ 0.2- 0.1_ D lJ___ H i; ILJ___1 0

1.50 0.5 1

Distance (x/D)

Figure 9. Predicted and measured constant velocity contours for flangedcircular opening (paper 1).

5.1.3 Three-dimensional openings

Plain rectangular exhaust openings are common basic opening types in industry and thus their proper simulation is important in many applications. Calculations were made for unflanged rectangular openings with aspect ratios 1:1, 4:3, 2:1 and 3:1 (paper 3). The predictions were compared to Dalla Valle’s experimental results (1952). The calculated velocity contours and centre-line velocities were in good agreement for openings with aspect

42

ratios 1:1 and 4:3. However, there were some deviations between the openings with larger aspect ratios. It was not known whether these deviations between the numerically predicted and the experimental velocities were due to the differences in the exhaust hood geometry or to the deficiencies of the numerical model. Therefore the air flow field was measured with the LDA for an rectangular exhaust duct with aspect ratio 2:1 (paper 4). The measured and the calculated velocity contours in symmetry planes are presented in Fig. 10.

Figure 10 indicates that except very close to the exhaust opening the predicted velocities are slightly higher than the measured ones. However, the differences are small. The average difference between the measured and calculated centre-line velocities is 3.5 %. Fletcher’s empirical equation (Table 2) deviated from the LDA measurements on an average by 8 %.

PREDICTEDMEASURED

Figure 10. Predicted and measured velocity contours for unflanged rectangular opening with aspect ratio 2:1 (paper 4).

Some of the difference between the present study and the previous results may be due to the fact that the numerically simulated case concerned a thick-walled rectangular duct, while in the previous studies the velocities were measured for rectangular tapered hoods connected to a circular duct. In these experiments the exhaust opening probably drew more air from the

43

region behind the opening. However, it can be concluded that the air flow field can be calculated accurately provided that the geometry of the simulations is similar to the actual case.

The air flow field was calculated also for a flanged rectangular opening with aspect ratio 1:2 (paper 1). The numerical computations were compared to the analytical solution presented by Tyaglo and Shepelev (1970) who derived equations for the three velocity components. In this model the velocities can be calculated analytically. With the flanged opening the numerically calculated velocities were also in good agreement with the analytical solutions. The numerically calculated centre-line velocities were within 5 % of the analytical values (Table 2).

In many cases the exhaust hoods may have a more complex shape than the basic types of circular and rectangular openings. It is therefore necessary to be able to predict also the air flow fields near such openings accurately. In paper 5 the calculated air flow field of a recently developed welding hood is compared with LDA-measurements. In the hood there are several slots to ensure even air distribution. The complex shape of the hood was approximated with parallelepiped cells and the locations and sizes of the slots were similar to those of the actual hood. The results show that the numerical calculations can be generalized to concern also arbitrary shapes with fairly good accuracy (Figure 11).

PREDICTED

MEASURED

y/D

Figure 11. Measured and predicted velocity contours for welding hood in vertical symmetry plane (paper 5) .

44

5.2 EFFECT OF AMBIENT AIR MOVEMENTS ON CAPTURE EFFICIENCY

5.2.1 Exhaust openings in a uniform air flow

Cross draughts are usually present in industrial applications of local exhaust ventilation systems and they will distort the airflow field calculated for the case where they are absent. In order to study the effect of ambient air movements on the performance of local exhaust hoods, numerical and experimental studies were made for unflanged rectangular and circular openings in a uniform flow parallel to the hood centre-line (papers 6 and 7).

In recent years potential flow theory has been used to develop models for predicting the capture efficiency of exhaust hoods under cross-draughts (Flynn and Ellenbecker, 1986; Conroy and Ellenbecker, 1989; Alenius and Jansson, 1989). The potential flow solutions predict capture efficiency which is a step function with values 0 or 1. Therefore an empirically determined spread parameter based on wind tunnel tests is used to estimate the dispersion of gaseous contaminants caused by turbulence (Flynn and Ellenbecker, 1986).

The capture efficiency for a given exhaust flow rate and cross-draught velocity depends on the location of the contaminant source relative to the exhaust opening. Therefore, for an accurate determination of the contaminant transport, several concentration fields must be calculated and thus requires a lot of computational time.

Contrary to the previous studies with the potential flow models, in this study the turbulent air flow fields were calculated first and the dispersion of gaseous contaminants due to turbulence was simulated using a stochastic particle tracking method. This method has the advantage over the potential flow models that the effect of turbulence intensity and scale on the hood performance can be simulated directly. Non-reacting submicrometer particles were released from a point source at different locations upstream the exhaust duct and the destination of the particles was determined. In the particle tracking method the computational effort depends on the numbers of particles released, but results with reasonable accuracy can be obtained in a relatively short computational time. The capture efficiency was calculated as the ratio of the number of particles captured by the exhaust hood to the number of those released. The estimates of the capture efficiency were based upon 1000 particle paths at each release point. The impact of the turbulence velocity fluctuations on the particle paths was simulated assuming the fluctuating velocity to be normally distributed with the variance proportional to the square root of the local turbulent kinetic energy.

45

This is a good approximation for the uniform supply air flow without mean velocity gradients. It is shown in paper 6 that, when the particle relaxation time is small compared to the characteristic eddy lifetime, the small particles will adjust almost instantly to air velocity and they follow the turbulent fluctuations accurately. The tracking of submicron particles is thus essentially equal to the tracking of fluid particles.

The numerical calculations were verified by tracer gas measurements conducted in the test room and by using a modified low-velocity supply air terminal for producing the uniform air flow. The cylindrical or rectangular exhaust duct with dimensions similar to those used in the simulations was positioned perpendicularly in front of the perforated panel outlet with a size of 0.68 x 1.2 m2. The velocity distribution of the air terminal unit was made uniform by installing a fabric felt filter downstream the perforated panel. The tracer gas was discharged at a constant rate through a 4 mm inside diameter tube at different locations between the supply air unit and the exhaust duct, and its concentration was measured far downstream in the exhaust duct by the FTIR-analyser.

Figure 12. Mean flow streamlines in the symmetry planes for rectangular opening (paper 6).

46

During the measurements the tracer gas release was moved at 1 cm intervals by means of a stepping motor. The capture efficiency was defined as

V = (31)Lo

where C is the measured tracer gas concentration in the duct at a given release point and C0 is the concentration when the source was held at the hood face.

Figure 12 shows an example of the mean flow streamlines for a free- stream velocity of t/5=0.44 m/s and the mean exhaust velocity of U0=3.0 m/s. Owing to the turbulent fluctuations particle dispersion occurs about the mean flow streamlines. This is illustrated in Fig. 13 where the trajectories of 10 particles released at each of three different points are plotted. These trajectories are based on the same flow field as shown in Fig. 12. The particles were released in the xy-plane at points where the predicted capture efficiency was 100, 50 and 0 %. The effect of turbulence on the particle paths is clearly seen. This kind of spread was also observed during flow visualizations made with smoke tubes.

Figure 13. Effect of turbulence on particle trajectories (paper 6).

47

U0 =5m/s

• U0 =2m/s

— CALCULATED

Figure 14. Predicted and measured capture efficiencies at various distances from the rectangular exhaust opening (paper 6).

The measured and the calculated capture efficiencies in the horizontal plane upstream the rectangular exhaust opening are shown in Fig. 14. The standard deviations of the measurements are indicated by vertical lines. With-

out turbulence the capture efficiency would be a step function with values of 1 and 0. The spreading of the particle tracks due to the velocity fluctuations causes spreading of the predicted capture efficiency curve, which is in accordance with the measured efficiencies. It can be seen that there is some asymmetry in the measured efficiencies, possibly because of spatial variations in the local supply air velocities. Nevertheless, the measured values are mostly in fair agreement with the predictions even at long distances from the exhaust opening, and the width of the effective capture region is quite well predicted. This is consistent also with the observations for the unflanged circular opening (paper 7).

The shape of the measured and calculated capture efficiency curves is similar to those observed by Jansson (1981) and by Flynn and Ellenbecker (1986). They derived the form of the curves assuming normally distributed or leptokurtic distribution of contaminants. In the present study the calculations obtained similar results by using the stochastic particle tracking method.

The ambient air flows may be very complex in industrial ventilation applications, and the assumption of isotropic turbulence with normally distributed velocity fluctuations used in this study is an idealization. The turbulent structures consist of a spectrum of eddies, while the calculation of the fluid flow rely on the Reynolds averaged equations of motion where averaging is done over all turbulence scales. This turbulence energy spectrum may be taken into account with more sophisticated alternatives such as LES, but they are computationally very demanding and therefore impractical for most practical problems.

The results suggest that the particle tracking method may be used to describe the transport of gaseous contaminants released at a small velocity and thereby to predict the performance of local ventilation systems. In these simulations, the capture efficiencies were predicted assuming a point source of contaminant, which did not affect the previously calculated flow field near the exhaust opening. In reality, contaminants may have momentum which must be taken into consideration in the flow field calculations.

The results also show that the control of contaminants can be significantly improved by blowing air through a low-velocity inlet on the opposite side of an exhaust opening. The particle dispersion increases with the turbulence intensity thus reducing the efficiency of the exhaust hood. Therefore low turbulence intensity and a uniform velocity distribution of the supply air is essential for an optimum performance of the system. During the measurements the capture efficiency was high even at distances of about x=5Am from the exhaust opening, where A is the hood face area. On the other hand, the disturbing air velocities in the test room were low during

49

the measurements. Higher cross-draught velocities as well as wakes caused by obstacles and workers in the flow field would be likely to reduce the performance of the system. Nevertheless, the use of local supply air with local exhaust may offer potential benefits for contaminant control.

5.2.2 Verification of a point sink model

In practice, it is often important to know the capture efficiency of a local exhaust hood under cross-draught, but numerical simulations are not feasible. The analytical potential flow solutions are convenient but they are restricted to infinitely flanged openings only. To model unflanged openings numerical techniques, such as the finite difference method or the boundary integral equation method (BIEM), are needed (Boyle et al., 1993; Yan et al., 1994) Thus there is also a need for a more simplified approach to obtain this information with a less complicated method, which could be directly used by designers.

A very simple potential flow model for an unflanged or flanged exhaust hood in a uniform air flow can be obtained by combining the air velocity fields of a point sink with a uniform flow. Heinsohn (1991) presented the stream function for an infinitely flanged point sink and a numerical method to calculate the streamlines, but he did not report any verifications of the model. The resulting flow is an axially symmetric flow, where the resulting velocity components are obtained by adding the velocities of a point sink and a uniform flow. If the velocity of the uniform flow in the negative x direction is Us and the point sink is located at the origin (Figure 15), the resulting flow field is then symmetric about the x axis and the axial velocity component is

U = qkits

q x

cos0 - U..2 A

kir (x2 + r2)3/2- u.

(32)

and the radial component

V =kirs2

sin6

kir (x2 + r2):3/2

(33)

where fc is 2 for a point sink in a plane (flanged opening) and 4 for an unflanged opening. A simple manner to determine the locations of stream-

50

(34)

lines is to integrate the velocities and compute the displacements:

x(t + At) = x(t) + UAt

r{t + At) = r(t) + VAt

The magnitude of the time step should vary with the velocity magnitude so that smaller values should be used close to the point sink. These equations describe the location at the time t+At when it is known at the time t. By repeating the process, the fluid streamlines from arbitrarily selected upstream locations are obtained (Figure 15). The unflanged exhaust duct can be at any location relative to the streaming flow, while for the flanged opening the only physically meaningful orientation is with the hood axis perpendicular to the flow.

POINT SINK UNIFORM FLOW COMBINED FLOW

EXHAUST DUCT

Figure 15. Combination of a point sink flow field with a uniform flowfield.

The stream function for this flow is in spherical coordinates (Heinsohn, 1991)

(35)

where s is the distance from the origin. The addition of a uniform flow with the sink flow creates a dividing streamline (Figure 15), so that the contaminants released inside the dividing streamline would be captured while the contaminants released outside would escape. The stream function

51

has value 'S'=q/(kir) at the dividing streamline and so its location can be found by expressing equation (35) in polar coordinates:

JL = Hlr2 -A_____£___ (36)k7T 2 k-K ^.2 + r2j1/2

This can be solved for r(x) giving, to the author’s knowledge, the previously unpublished result

2q _ x2 ^ xq kitUsx' 2 IkitU,1/2

k-KJJs 2 kirUs 2 q Q

The distance from the hood opening to the dividing streamline for a hood in uniform flow perpendicular to its axis is thus

r( 0) = 2 qkirUs

1/2(38)

This type of dependence of capture efficiency on the exhaust flow rate and cross-flow velocity has also been seen by Fletcher and Johnson (1986), who determined the capture efficiency of a flanged square exhaust hood in a cross flow.

1.5CFD PREDICTED STREAMLINES

r/D

POINT SINK PREDICTED STREAMLINES

1.5

Figure 16. Example of mean streamlines for a circular opening (upper half) and for a point source (lower half) with q=0.042 m3/sand Us=0.44 m/s.

52

The streamlines obtained using the simple potential flow model are shown with the numerically predicted mean flow streamlines for an unflanged duct in coaxial airflow in Figure 16. The behaviour in general is similar, but there are some differences between the idealized model and the CFD calculations. It may be seen that the location of the dividing streamline is closer to the centerline with the point sink model than it is with the CFD model.

The distances calculated by Equation (36) are compared with the measured values in Figure 17. The distances are normalized with the equivalent diameter De, which is equal to 4 times the cross sectional area divided by the duct perimeter. In the same figure are plotted results from previous wind-tunnel studies made by Li-Qiang (1984) and Flynn and Ellenbecker (1986). In both cases the cross draught velocity was perpendicular to the hood centre-line. Li-Qiang made his measurements using smoke tests, while in the other studies the results are obtained from tracer gas measurements and correspond to locations where the measured capture efficiency is 50 %. Figure 17 shows, that although there is scatter in the measurements, the variations can be estimated fairly well.

■ Unflanged rectangular (Li-Qiang, 1984)

• Flanged circular (Flynn and Ellenbecker, 1986)

d Unflanged rectangular (present study)

o Unflanged circular (present study)

— Curve fit

0 12 3

Measured r/De

■ calc = 0.984 Tmeas

FT = 0.9186

Figure 17. Comparison of theoretical and experimental streamline distances from the x-axis.

53

The results of the potential flow model are restricted to cases where the cross-draft velocity is uniform, the flow field is unobstructed, and the effect of the momentum of the contaminant source on the flow field is negligible. It is likely that the model is most accurate for circular ducts or rectangular openings with aspect ratios near unity. In industrial halls the air velocities may be unsteady and vary in magnitude and direction. The turbulence intensities are also higher than used in study: Hanzawa et al. (1987) measured intensities in various ventilated spaces which were from 10 % to 70 %. The contaminant dispersion increases with the turbulence intensity resulting in more wider capture efficiency curves. However, despite its limitations the simple potential flow model may be useful in determining the performance of exhaust hoods. The model accounts for the effects of cross-draughts in an explicit, quantifiable manner and allows a quick way to estimate the effective control range of an exhaust hood if the magnitude and direction of the cross-draught velocity are known. This is a clear advantage over the present capture velocity approach, which does not take quantitatively into account the ambient disturbances.

54

5.3 EFFECT OF CONTAMINANT SOURCE MOMENTUM ON CAPTURE EFFICIENCY

Many industrial operations produce contaminants which are generated by a high temperature process. When such contaminants are controlled with local exhaust, the resulting flow field is then formed by the complex interaction of the exhaust flow field and the highly turbulent buoyant plume. Although much experimental and theoretical work has been done on turbulent buoyant plumes, little is reported on the simultaneous modelling of plumes and local exhaust ventilation and the previous studies have relied on scale model or full-scale experiments (Goodfellow, 1985). Freeh and Scholer (1993) calculated the combined flow field for a circular exhaust hood located over a heat source, assuming axially symmetric situation, but no experiments were made to verify the simulations.

In this study the air flow field of a lateral hood exhausting near a hot contaminant source was calculated and the results were verified with air velocity and capture efficiency measurements. It is known that the k-e model used in the simulations does not perform very well in predicting turbulence quantities in strongly buoyant flows with anisotropic turbulence characteristics. However, because of its popularity, it is important to clarify the k-e model’s reliability when it is applied to buoyant flow simulations.

The air velocity and capture efficiency measurements were made in the test room. A 0.20 m x 0.10 m unflanged rectangular duct was installed in the middle of the test room at the height of 1.0 m above the floor. The heat source mounted in front of the exhaust duct was a soldering iron with a convective heat release rate of 100 W. The soldering iron was used as a heat source only and no actual soldering operations were made during the experiments. The vertical temperature distribution in the test room was measured with thermistors at six different heights between 0.5 m and 2.5 m above the floor. During the experiments the vertical temperature gradient was quite small, about 0.1 K m"1.

In the experiments the capture efficiency was measured using the tracer gas method. Capture efficiencies were measured at three distances between the heat source and the hood face (0.20, 0.25 and 0.30 m) with several exhaust flow rates. In addition, the air velocities in front of the exhaust duct were measured with the LDA, when the distance between the hood and the heat source was 0.20 m. Velocities were measured on the hood centre-line in the vertical and horizontal directions.

In order to check out the reliability of the measurement system and the applicability of the numerical simulations when calculating plumes, measurements were also made for the pure buoyant plume. In these measure-

55

SYMMETRY PLANE

EXHAUST DUCT

HEAT SOURCE

□

z

X

Figure 18. Geometry of the measured and the calculated cases.

ments vertical velocities were measured with the LDA at six vertical levels above the heat source without the local exhaust.

In the simulations an unflanged rectangular opening with dimensions identical to those used in the experiments was exhausting laterally. The geometry of the simulated case is shown in Figure 18. The heat source was modelled with rectangular cells with a surface area close to the soldering iron used in the measurements. Symmetry was assumed in the vertical midplane. Two non-uniform calculation grids were used in the simulations with grid sizes of 32 x 21 x 36 and 62 x 32 x 62 cells. A uniform velocity was assumed in the exhaust duct and a fixed pressure at freestream boundaries. A heat flux boundary condition was specified on the surface of the hot source so that the convective heat release rate was 100 W. The heat exchange due to radiation was omitted. After solving the air velocity field the capture efficiency was calculated using the particle tracking method.

Due to the computer resource limitations further grid refinements were not possible. On the other hand, the required grid densities for the exhaust hood in isothermal cases are known from the previous studies (papers 3 and 4). Therefore the grid dependency was studied separately for the buoyant plume. These calculations were made using both three dimensional rectangular and cylindrical co-ordinate systems. With cylindrical co-ordinates axial symmetry could be assumed under calm ambient conditions, and the axis of the soldering iron coincided with the z-axis. In this geometry the grid refinement tests were made using 62 x 32, 82 x 42, 162 x 82 and 322 x 162 non-uniform grids.

56

W{m

S'1)

1.4

W = 3.3 (■

MEASURED

AXISYMMETRIC 62 x 32 RECTANGULAR 62 x 32 x 62 AXISYMMETRIC 82x42 AXISYMMETRIC 162x82 AXISYMMETRIC 322 x 162

Figure 19. Predicted and measured plume centre-line velocities above the heat source. Ds is the heat source diameter.

The measured and the predicted mean centre-line velocities for the pure plume are plotted in Fig. 19 versus the distance z/Ds from the heat source. The mean velocities with local exhaust are shown in Figs. 20 and 21. In Fig. 22 is the comparison of the predicted and the measured capture efficiencies.

Previous plume flow studies (Shabbir and George, 1994) have shown that for the round plume in a uniform environment the mean vertical velocity W varies in the decay region as

gQpTcp

1/3

Z^expi-B^rlz)2) (39)

where g is the magnitude of the gravitational acceleration, Q the convective heat release rate and z is the vertical distance above the virtual origin of the plume. A curve fit of the measured velocities gives Av = 3.3 and Bu = 57, which are in close agreement with the values of 3.4 and 58 obtained by Shabbir and George (1994) in their more extensive plume measurements. The curve fit is plotted in Fig. 19 with a dashed line.

Figure 19 shows that the fluid rapidly accelerates to a high velocity over a short distance and then starts to decelerate. The effect of the grid refine-

57

ment on velocity profiles is shown in the same figure. Very fine calculation grids are needed for grid independent results. A failure to provide enough mesh in the plume will result in the plume flow being insufficiently resolved, so that the momentum is rapidly and artificially diffused causing too low centre-line velocities near the heat source . It can be estimated from the axisymmetric calculations that in three dimensions the grid size should be about 160 x 80 x 160 to achieve grid independent results, when symmetry is assumed only about the vertical mid-plane. This means that the number of cells required is over two million, which is seventeen times the number of cells used in this study highlighting the substantial computing requirements demanded by the three-dimensional analysis of this type flow.

An example of the measured and the predicted mean horizontal velocities on the hood centre-line is shown in Figure 20 and vertical velocities in Figure 21. The results are for the situation where the heat source was on. The calculated horizontal centre-line velocities were in fairly good agreement with the measured values, but in the vertical velocities there were some discrepancies between the predictions and the experiments.

q = 0.066 m s• MEASURED

-------GRID 32x21----- GRID 62 x 32

0.20 m

Figure 20. Predicted and measured horizontal velocities on the hood centre-line.

With the lower exhaust flow rate the predicted maximum vertical velocity above the heat source was lower and the velocity profile was wider than the measured one. A similar situation may be anticipated also from the

58

pure plume calculations. When the exhaust flow rate is increased, the plume bends towards the hood and both the calculated and the measured vertical velocities become lower.

The experimental and the calculated capture efficiencies are shown in Figure 22. The standard deviations of the measured efficiencies are indicated by vertical bars. Capture efficiency depends on both the separation distance and the exhaust flow rate, as expected, and this trend could also be detected in the simulations. However, the predicted capture efficiencies were clearly higher than the measured ones. The calculations gave exhaust flow rates, which were 40 - 50 % lower than was actually required for an efficient contaminant control. The discrepancies are likely due to the underprediction of the vertical velocities caused by the heat source and turbulence intensities in the plume region, which results in the underestimation of the contaminant dispersion. Another reason for the quite poor capture efficiency predictions may be that the simulations assumed no disturbances at the freestream boundaries. In reality, the ambient air currents in the test room may have reduced the efficiency. It is also possible that more complicated turbulence models give more accurate results, but the confirmation of this awaits finer grid solutions.

_ q = 0.032 m s

0.20 m

••••

MEASURED

GRID 32 x 21 x 36

GRID 62 x 32 x 62

Figure 21. Predicted and measured vertical velocities on the hood centreline.

59

CA

PTU

RE

EFFI

CIE

NC

Y (%

)

EXHAUST FLOW RATE (m3 s1)

MEASURED

O X = 20 cm n x = 25 cm A x = 30 cm

CALCULATED

• x = 20 cm ■ x = 25 cm a x = 30 cm

Figure 22. Measured and calculated capture efficiencies. Calculation results are shown by solid lines and experimental results by symbols.

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5.4 USE OF A LOCAL SUPPLY AIR

The applicability of numerical simulation in the design of local ventilation with auxiliary air was studied by calculating air flow and concentration fields for a local ventilation unit (Halton Comfo LCI 1000). The local ventilation unit was equipped with local supply and exhaust ventilation. The supply air unit was placed above the worker and its purpose was to reduce his or her exposure to airborne contaminant by providing clean air. After developing a verified model, calculations and experiments were made to find an optimum configuration for the local ventilation unit, when it was applied to hazardous powder handling operations.

A three-dimensional, rectangular calculation grid was used in the simulation of the local ventilation unit. The size of the non-uniform grid was 35 x 24 x 35 and it was finer near the exhaust and inlet openings. Constant values for the velocity components were given at the inlet and exhaust openings. A vertical symmetry plane was used at the centre-line to reduce the number of computational cells.

The calculations were verified by air velocity and tracer gas measurements made in the test room. In the measurements, tracer gas was injected into the air inlet duct and a fan in the test room ensured that it was mixed with room air. The tracer gas concentration and air velocity were measured at two different heights (1.5 and 1.1 m above the floor) in three vertical planes.

A comparison between the calculated and the measured velocities and the fractions of local supply air in the vertical symmetry plane is shown in Fig. 23. The standard deviations of the measured concentrations are indicated by vertical bars. According to the predictions, there should be a region below the supply air unit, in the worker’s breathing zone, where the fraction of clean supply air is near unity. This is desirable in order to protect against ambient air contaminants as well as against contaminants generated at the working table. The fraction of clean air decreases in a region underneath the outer edge of the supply air unit where ambient air is mixed with supply air. The predicted velocities are uniform and fairly low at the height of 1.5 m, whereas at the height of 1.1 m large velocity gradients are observed near the exhaust opening.

It can be seen in the Figure 23, however, that when the local ventilation unit was operating normally the agreement between the predicted and the measured values is poor. The measured velocities were over 0.5 m/s, and were outside the range of the velocity transducer used in the measurements, while the calculated values were about 0.2 m/s. Furthermore, the measured supply air fraction below the supply air unit was also less than predicted.

61

z=1.5 m

0.3 0.5 0.7 0.9 1.1 1.3 1.5

> 0.1

0.3 0.5 0.7 0.9 1. 1.3 1.5

z= 1.1 m

0.3 0.5 0.7 0.9 1.1 .3 1.5

V 0.4

L»> 0.1 •

0.3 0.5 0.7 0.9 1. 1.3 1.5

2=1.1 m

a Perforated plate * Perforated plate + filter

— Calculated

Figure 23. Measured and calculated velocities and supply air fractions in the vertical mid-plane.

In the simulation, a uniform velocity profile was assumed downstream of the local supply air unit, which was equipped with a perforated plate. This assumption turned out to be unwarranted and lead to unrealistic results. Therefore the velocity distribution was made more uniform by using a fabric felt filter downstream of the perforated plate in the supply air unit. After this modification a more constant velocity profile was obtained below the supply air unit, as may be seen from the results in Fig. 23. This also resulted in a good agreement between the predicted and the measured concentrations.

The use of local supply air may provide desirable protection against contaminants, but it may also increase the risk of draught. The sensation of draught can be estimated by an empirical expression, which takes into consideration the combined effect of mean air velocity, air temperature and turbulence (Fanger et al., 1988). For the perforated plate the measured velocities and velocity fluctuations below the supply air unit were signifi

62

cantly higher than for the fabric filter. The average percentage of dissatisfied persons calculated from different measurement points at the centreline was 38 % for the perforated plate with the supply air flow rate used in the investigations. When the filter was installed, the predicted percentage of dissatisfied persons was only 13 % at the same supply air flow rate. This seems to lead to the conclusion that the fairly constant velocity profile obtained by the use of a filter at the supply outlet not only increases the protection factor against ambient air contaminants but also improves the thermal comfort of the local ventilation unit.

The measurements and numerical simulations in paper 8 were restricted to conditions where the worker was absent. In order to study the effect of the local supply air under more realistic working conditions the worker’s exposure was measured during manual handling of flour additive powder (paper 11). In the same study the optimum location of exhaust openings was investigated numerically and experimentally. Five different local ventilation configurations were modelled: (1) a downdraught hood between the worker and the working table (Case 2); (2) a sidedraft hood at the opposite side of the working table (Case 3); (3) a downdraught hood in combination with local supply air (Case 4); (4) a sidedraft hood in combination with local supply air (Case 5); and (5) sidedraft and downdraught hoods in combination with local supply air (Case 6). Case 1 was the situation with dilution ventilation only, and it was not modelled. In each case the sum of local and general ventilation flow rates was constant (0.40 m3/s).

Table 6. Studied configurations. During the experiments the local and the general supply air flow were isothermal.

Case Local exhaust flow rate

(m3/s)

Localsupplyflowrate

(m3/s)

General ventilation flow rate (m3/s)

Dust concentration

(mg/m3)

Downdraft

Sidedraft

Supply Exhaust Mean SD

1 0 0 0 0.40 0.40 42 7.4

2 0.20 0 0 0.40 0.20 0.7 0.29

3 0 0.20 0 0.40 0.20 0.8 0.45

4 0.20 0 0.14 0.26 0.20 0.2 0.14

5 0 0.20 0.14 0.26 0.20 0.3 0.23

6 0.10 0.10 0.14 0.26 0.20 0.08 0.05

63

The breathing zone dust concentrations were measured by gravimetric sampling and real time monitoring during the simulated manual weighing of flour additive powder. The studied configurations and the resulting breathing zone concentrations are shown in Table 6. Examples of the calculated velocity fields in the symmetry plane and the measured concentrations in three different cases are shown in Fig. 24.

0.14 m/s

0.10 m/s

0.2 irr/s

0.24 mg/m'CASE 4

0.1 m3/s

CASE 6 0.08 mg/m

Figure 24. Predicted constant velocity contours in the vertical symmetry plane and measured breathing zone dust concentrations.

64

The experiments showed that using only local exhaust, the breathing zone concentration could be reduced by 98 % from the concentration measured with only the general ventilation. According to the numerical simulations, local supply air creates a downward airflow pattern that directs contaminants away from the breathing zone and thus improves worker protection. This was also confirmed by the measurements, in which the combination of supply and local exhaust resulted in a further statistically significant decrease in exposure. The best results were clearly achieved when both exhaust inlets were used in combination with local supply air. With this configuration the reduction in exposure was over 99.8 %. Such a high control is needed for example in bakeries, where enzyme-containing flour additive powders are handled. These strong sensitizers are a likely reason for the increased prevalence of respiratory symptoms among bakery workers. Interestingly, this reduction was obtained without increasing the exhaust airflow rate.

During the experiments dust was mainly generated by strewing the flour additive powder into the receiving container. The real-time monitoring data showed how the worker’s movement induced air currents causing the contaminated air to move from the receiving container into the worker’s breathing zone. It is assumed that this dust-laden air was captured by the downdraught hood between the worker and the working table. The findings suggest that by dividing the exhaust into two inlets, the contaminants generated during the pouring operation were captured quite effectively by the sidedraft hood, and the escaping dust travelling towards the worker was in turn controlled by the downdraught inlet and kept away from the breathing zone by the vertically flowing supply air.

The results proved that the air flow and the concentration fields can be solved numerically with reasonable accuracy, provided that the boundary conditions are realistic. The results also showed, how the use of a low- velocity supply air system installed above the work station makes it possible to create regions of clean air and to reduce the worker’s exposure without impairing thermal comfort. However, to achieve high protection the supply air velocity distribution must be uniform.

The simulations were restricted to cases where the worker was absent. The real-time monitoring data showed that the worker’s movements may strongly influence the exposure level. However, these steady state simulations are useful in providing better understanding of airflows and in helping to design more efficient local ventilation systems.

The calculations differed from the actual conditions because they did not take into consideration the convective heat release rate from the worker. The convection creates boundary layers around the worker, which entrain air from the surroundings, so that the flow rate increases in the upward

65

direction. Measurements made with person simulators have shown that in unobstructed conditions the convection flows above the simulated persons are about 0.02-0.04 m3/s and the maximum velocities are about 0.2 m/s at the height where the local supply air unit situated (Mundt, 1996). The velocities induced by the convection were negligible near the contaminant source compared to the velocities created by the local supply and exhaust. However, the convection may have affected the exposure by transporting contaminants entering the body boundary layer towards the breathing zone.

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5.5 WAKE EFFECTS ON THE WORKER’S EXPOSURE

In order to investigate the reliability of the simulations when modelling the worker’s effect on the performance of local ventilation systems calculations were made where the worker was placed in a horizontally unidirectional air flow. Such flow is used in several industrial operations to control airborne contaminants (George et al., 1990; Andersson et al., 1993; Guffey and Barnea, 1994). This kind of ventilation is used also in some non-industrial applications like in indoor firing ranges. However, when a person is in a unidirectional airflow, a region with a recirculating air flow can be created downstream that person. Recent studies have shown that if the contaminant source and the breathing zone are within this near wake region, high exposure may occur (Kim and Flynn, 1992).

Although the flow past simple geometries has been widely investigated, there are not many numerical and experimental studies on the airflow around a worker. Most of the reported simulations are made assuming two- dimensional flow and modelling the worker as an ellipse (Flynn and Miller, 1991; Ingham and Yuan, 1992; Dunnett, 1994; Flynn et al., 1995). However, experiments have shown that the flow around the worker in a uniform airflow is three-dimensional (Kim and Flynn, 1991a), and therefore the airflow in the wake region may not be adequately described with two-dimensional models.

Previous investigations have studied the exposure when the contaminant source was fixed or the distance varied at the height of the chest only (Ljungqvist, 1979; George et al., 1990; Kim and Flynn, 1991b ). In this study the effect of the contaminant source location on the worker’s exposure was examined more thoroughly when the source location was varied within the near wake region. Extensive wind-tunnel measurements were made to study this phenomenon and to verify the calculations (paper 9).

In the simulations, the flow field was solved assuming steady and isothermal flow employing the standard k-e turbulence model. The calculations were performed with two non-uniform grids of 41x11x29 and 41 x 20 x 29 points to study the effect of the grid refinement on the results. A vertical symmetry plane in the centre-line was introduced to reduce the number of grid points. The mannequin was modelled with rectangular cells. A uniform velocity was assumed at the rear end of the tunnel and a fixed pressure at the tunnel face. After solving the flow field the worker’s exposure was predicted by particle tracking assuming that submicron particles are transported in the same way as gaseous contaminants. This method does not give direct information on the contaminant concentrations but it is valuable in estimating the variations in the breathing zone concentration due to different release points and also in predicting the efficiency of possible control measures. The estimates of the worker’s exposure were

67

based upon 1000 particle paths from each release point. In the calculations the same release points were used as in the experiments.

The worker’s exposure due to a recirculating flow was determined in open- ended tunnel measurements, when the location of the contaminant source in the near wake region of a mannequin was varied. The effect of the contaminant source location on the worker’s exposure was examined by releasing tracer gas from 420 different points within the wake region downstream the mannequin and measuring the breathing zone concentration with three different mean freestream velocities (0.25, 0.375 and 0.5 m/s). Every freestream velocity was tested twice, and the averages of the concentrations were calculated.

The measured and the calculated relative exposures in the vertical midplane are compared in Figure 25. These results are also normalised using the highest concentration observed when the exhaust airflow rate was 1.5 m3/s.

SZ

f=

Ug =0.25 ms 1 Uq=0.375 ms 1 =0.50 ms 1

1.20.6 0.4

x (m) x (m) x (m)

MEASURED

PREDICTED

Figure 25. Measured relative exposures and predicted relative particle counts in the vertical mid-plane with various mean freestream velocities (paper 9).

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This maximum concentration occurred when the release point was on the mid-plane 20 cm from the mannequin at a height of 1.2 m. The results showed that the breathing zone concentration depends on the height and on the distance of the contaminant source from the body as well as on the distance from the vertical mid-section. Considering the experimental scatter in the measurements the overall agreement between the predictions and the experiments was quite good. The height and the length of the recirculating region in the vertical mid-plane was well predicted. Moreover, the location of the contaminant release point producing the highest concentration was correctly predicted. The length of the region where significant contaminant transport occurs into the breathing zone (over 10 % of the reference concentration) was about 0.5 - 0.6 m and it was not much affected by the free- stream velocity.

The calculated mean velocity vectors in the vertical mid-plane and a horizontal plane at the height 1.1 m are shown in Fig. 26. This flow pattern is also in good agreement with the visual observations reported by Kim and Flynn (1991a). The predicted regions causing 10 % and 80 % of the reference exposure are also overlaid in the vertical mid-plane. From these figures the flow pattern in the reverse flow region can be clearly seen. For clarity, the length of the velocity vectors is proportional to the square root of the velocity magnitude. These mean air velocity fields also help to understand the contaminant transport into the breathing zone and to explain the measured exposures. In the vertical section approximately above the mannequin’s hip level (z>0.8 m, Fig. 26) the air circulates clockwise and

/ 0.1 V

PLAN VIEW

l-------------- 1-------------- 1-------------- 1--------------10 0.2 0.4 0.6 0.8

x (m)

Figure 26. Predicted air flow in the vertical mid-plane and a horizontal plane with a mean Jreestream velocity of 0.375 m/s.

69

contaminants released in this region may enter into the breathing zone. On the other hand, below the hip level the air circulates mainly horizontally and the contaminants released in this region do not enter significantly into the breathing zone.

An increase in the grid density did not affect the predicted velocities much, although the recirculation length was somewhat higher with the coarser grid. It is difficult to say whether grid independent solutions were obtained because further refinements in the grid density were not possible due to the limitations of the computer resources.

The flow field downstream the worker is very complex and the results revealed that the exposure depends greatly on the location of the contaminant source. Recent studies have indicated that the standard k-e model may not adequately predict the flow past bluff bodies (Obi et al., 1990; Franke and Rodi, 1991; Murakami et al., 1991). The inaccuracies are due to the shortcomings of the eddy viscosity model in predicting the quantities in that kind of flow (Murakami et al., 1991). Better agreement with the measured flow fields were obtained with the Reynolds stress models, which take the turbulence anisotropy and flow history effects on the turbulence into account. However, even these more sophisticated models were not fully satisfactory, and it was concluded that the most accurate results may be obtained using the large-eddy simulation (LES). The LES is considered to be a potentially promising method, but so far the very large computational resource requirements have limited its application to research topics. On the other hand, the differences between the geometry of the mannequin in reality and in the simulations, spatial variations of the flow velocities, and possible periodicities of the flow may have greater effect on the results than the turbulence model.

Despite the deficiencies of the simulations the variations in the worker’s exposure could be predicted quite well in the centre-line assuming a steady flow. The contaminant source position which caused the greatest exposure was predicted surprisingly well. An important feature in the near wake region is the recirculation zone downstream the worker, because contaminants released in this region can enter into the breathing zone. The size and location of this region were also predicted well. The relatively good agreement between calculations and experiments implies that the three-dimensional steady state simulations can give meaningful results when predicting the flow field in this region.

The results are applicable when a stationary worker is in a uniform airflow and the momentum of the contaminant source is negligible. These restrictions are rarely met under actual working conditions. The calculations also neglected the convective heat release rate from the worker, which may affect the flow pattern in the recirculation zone. Moreover, Kim and Flynn

70

(1992) proved that the contaminant source momentum can significantly affect the airflow field and the worker’s exposure. However, the results are useful in understanding the transport of contaminants in the near wake region and in designing efficient control techniques.

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6 CONCLUSIONS

The aims of this study were to study the possibilities and limitations of CFD simulations as a design tool for local ventilation. In addition, it examined the applicability of potential flow solutions in modelling exhaust openings. The most important factors affecting the efficiency of local ventilation systems were identified and their effect on the efficiency was investigated systematically in some representative cases. The results of the simulations were also used to improve the performance of local ventilation systems.

The results proved that stationary isothermal air flow and concentration fields near local ventilation systems can be predicted fairly accurately using the common k-e turbulence model. However, in the buoyant flow simulations the accuracy was only satisfactory. The discrepancies between the predictions and the experiments concerning non-isothermal flow may have been due to the inability to reach grid-independent solutions and due to the deficiencies of the turbulence model. In flows near unobstructed exhaust openings, where the turbulence stresses are negligible, potential flow solutions are sufficient. To estimate the effective control range of exhaust hoods operating in the presence of an idealized uniform cross-draught a simple potential flow solution can be used provided the magnitude and the direction of the cross-draught are known.

The results showed also that the use of uniform low-velocity local supply air in combination with local exhaust offer significant benefits in protecting the worker from airborne contaminants as well as in increasing the effective control range of exhaust hoods. More research is needed to study the performance of these kinds of systems in actual operating conditions.

The accuracy of the simulations usually depends on several components of the simulation method, such as the applicability of the adopted turbulence model, the computation grid, the reliability of the boundary conditions and the discretization scheme. In these studies the factors having the greatest effect on the accuracy were caused by the limitations of computer resources and the shortcomings of the k-e turbulence model. To obtain grid independent solutions for strongly buoyant flows typical to industrial applications very dense calculation grids are needed. The results also revealed that the worker’s movements may strongly influence the exposure level. To describe these effects, the time-dependent flow should be solved and this would require unpractically long and expensive calculations on available computers. Nevertheless, the results suggest that the computing power and the present turbulence models can already provide realistic simulations of several practically important cases.

The calculations in this study were made with one computer code only. The FLUENT code was used because of its availability and user-friendli

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ness. Furthermore it employs the same differencing methods, discretization schemes, turbulence models and other computation techniques as are widely used in other commercial and non-commercial codes. It is thus likely that the results obtained have more general applicability.

The CFD simulations are in principle superior to present design methods because they can quantitatively take into account the various factors affecting the performance of local ventilation systems. With the aid of properly made simulations the economic optimization of contaminant control methods is possible without extensive experimentation. The possibilities of numerical modelling increase steadily due to the rapid development of computer technology and due to the increasing sophistication of CFD codes. It is likely that the incorporation of CFD simulations into the design process will result in improved understanding of the interaction between different factors and in the design of better local ventilation systems.

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Paper 1

NUMERICAL CALCULATION OF AIR FLOW FIELDS GENERATED BY EXHAUST OPENINGS

Ilpo Kulmala*Tampere University of Technology, P.O. Box 537, SF-33101 Tampere, Finland

(Received 11 May 1993 and in final form 22 July 1993)

Abstract—The applicability of numerical simulations for the prediction of the flow field of exhaust openings was examined. Numerical calculations were conducted for two-dimensional plain and flanged slots, plain and flanged circular openings and three-dimensional plain and flanged rectangular openings. The air flows were simulated by the FLUENT computer code based on the finite difference method, using the k-e turbulence model. The accuracy of the simulations was determined by comparing the predicted results with potential flow solutions and experimental results. For flanged openings, the agreement between numerical simulations and potential flow solutions was good. For plain openings the agreement was satisfactory.

NOMENCLATUREA area of exhaust openinga half-length of rectangular exhaust openingb half-width of rectangular exhaust openingC„ empirical constant in k-e turbulence model D diameter of circular openingE empirical constant in log law, 9.0 in case of smooth wallb] body forcek turbulence kinetic energyL length of rectangular openingP mean pressureR radius of circular openingUt stream wise velocityu + non-dimensional streamwise velocityw, mean velocity component in direction x,u\ fluctuating component of velocity component in direction xt u, v, w velocity components in x, y, z directions

v, velocity components in r, z directions in cylindrical co-ordinates velocity vectormagnitude of velocity at a point mean velocity at the hood face width of rectangular opening complex number in the w plane

x, y, z Cartesian co-ordinatesXj Cartesian co-ordinates in tensor notationy+ non-dimensional distance from wallz complex number in the z plane

<5,j Kronecker delta, dtj = 1 for i=j and 0 otherwise£ turbulence dissipation ratek von Karman’s constant, 0.42ti dynamic viscosityp, turbulent viscosityv kinematic viscosity

*On leave from Technical Research Centre of Finland, P.O. Box 656, SF 33101 Tampere, Finland.

452

fluid density velocity potential wall shear stress

I. Kulmala

P<t>

INTRODUCTION

A properly designed local exhaust ventilation system is an effective way of controlling airborne contaminants in the workplace. The contaminant transportation and thus the local ventilation efficiency is greatly affected by the flow field generated by exhaust openings, so that in the design of local exhaust ventilation it is essential to be able to predict the air flow fields accurately. However, the equations governing turbulent air flow are complex and usually cannot be solved analytically. As a result the design of local exhaust is traditionally based on empirical equations and thus lacks a deeper insight in the underlying physical phenomena.

In recent years models based on potential flow theory have been developed for predicting the air flow fields near exhaust openings. There are now analytical models both for flanged rectangular and for flanged circular openings, and for a plain slot. Numerical models have been used to solve air flow fields for two-dimensional and cylindrical symmetrical cases. The models approximate air flow into unobstructed exhaust openings satisfactorily, but models based on potential flow theory are unable to describe those turbulent flows which are of a great practical importance.

Computational fluid dynamics (CFD) has been applied extensively for predicting the turbulent air flow and concentration fields in ventilated spaces (Awbi, 1991). In industrial ventilation numerical simulations have been more uncommon. Heinsohn and Choi (1986) calculated two-dimensional turbulent velocity and contaminant concentration fields for a push-pull ventilation system, using Schlieren photographs to evaluate the validity of the calculations. Braconnier et al. (1991) studied numerically the effects of cross-draught on the capture efficiency for an exhaust system of a surface treatment tank and the results verified with velocity and tracer gas measurements, but CFD has been used much less often to model local exhaust ventilation than to model the ventilation involved in comfort.

As the performance of computers and the reliability of numerical models increases more complex fluid flow problems can be solved, though in practice it is often difficult to verify the results of numerical calculations and the accuracy of the predictions is crucially affected by the boundary conditions applied. The aim of this study was to determine the applicability and limitations of numerical simulation when calculating exhaust openings. Isothermal, turbulent air flow fields were calculated for different kinds of unobstructed openings and the results were compared with previous potential flow solutions or with experimental results.

THEORY

Irrotational, incompressible and frictionless fluid flow can be described by potential flow theory, in which there exists scalar velocity potential so that

V = V^. (1)

Substituting the conditions imposed by continuity gives Laplace’s equation

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Numerical calculation of air flow fields 453

V2</> = 0. (2)

This equation, taken in conjunction with appropriate boundary conditions, can be solved analytically or numerically to give the ideal flow field.

Several researchers have developed analytical solutions for different kinds of openings. The first air flow model for an infinitely flanged rectangular opening was presented by Tyaglo and Shepelev (1970), and later validated by Flynn and Fitzgerald (1989). A potential flow model for an infinitely flanged circular opening was derived by Drkal (1970), and a model with empirical modifications by Flynn and Ellenbecker (1985,1987). In most cases there seemed to be good agreement between experimental and theoretical air velocities.

For an arbitrarily shaped configuration there is no analytical solution. When the potential functions of the flow field are unknown, numerical methods may be used to obtain the solution of the flow field. Flow fields have been modelled by a finite difference method (Anastas and Hughes, 1989; Anastas, 1991; Flynn and Miller,1988) , by a finite element method (Garrison and Wang, 1987; Garrison and Park,1989) and by a boundary integral method (Flynn and Miller, 1988). In the numerical solution, the major difficulty is to determine appropriate boundary conditions. Anastas (1991) has demonstrated such difficulties when calculating flow fields of initially unknown boundary conditions. He attempted to solve numerically the velocity field for a plain slot by determining the constant velocity contours using a continuity equation. Despite of the very reasonable initial boundary conditions the solution did not converge.

In practice, owing to recirculation of air, and to plumes, jets and obstacles in the velocity field, the flow field can not be described satisfactorily by potential flow. In order to predict the turbulent flow one has to solve the governing continuity and the momentum equations. The time-average steady-state equations using tensor notation are

(3)dx,

dui dP d+ -=-/*! (4)

where w, is the velocity in the direction x£, P is the pressure, p is the dynamic viscosity, p

is fluid density and Fi is body force. In general, for the appropriate boundary conditions these complicated non-linear partial differential equations have no analytical solution. In Equation (4) the last term on the right-hand side represents the effect of the velocity fluctuations on the mean flow and are called Reynolds stresses, which must be represented by a suitable turbulence model in order to solve the momentum equation. If isotropic turbulence is assumed, they can be expressed by the following equations

(5)

in which is the Kronecker delta and k is the mean turbulent kinetic energy per unit volume of fluid

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454 I. Kulmala

k =12

(6)

The most widely used turbulence model is the k-e model, which has been used successfully since the 1970s (Launder and Spalding, 1974). In it the turbulent viscosity pt is related to the kinetic energy of turbulence k and the dissipation rate of kinetic energy e by the equation

fh = , (7)

where is a constant (usually Cu = 0.09). When determining a flow field, additional partial differential equations for k and e must be solved with the continuity and momentum equations.

Due to the damping effect of the wall the transport equations do not apply to the viscous sublayer close to a solid wall. The effect of the walls on the transport equations is therefore usually computed by the wall function method. In the absence of a pressure gradient, within the turbulent boundary layer the velocity is related to the wall shear stress by (Launder and Spalding, 1974)

u+ =-ln(£> + ),K

where the dimensionless velocity u + is defined as

\Aw/P

and the non-dimensional distance y + from the wall

y ~ v ’

where Ux is the resultant velocity parallel to the wall, tw the wall shear stress, p is the fluid density, k is the von Karman’s constant {k = 0.42) and £ is a roughness parameter (E—9 for hydraulically smooth walls). This logarithmic law of the wall is sufficiently accurate for most cases when the non-dimensional distance is in the range 30 <y + < 100 (Rodi, 1984). Where the velocity varies greatly, this criterion can not be satisfied at all points adjacent to the walls. In these situations the distance should be correct at points where the shear stress has the greatest significance.

In computational fluid dynamics the calculation domain is divided into number of grid points and the above equations are discretized. A method commonly used in CFD is the finite volume (finite difference) method. The discretized equations are solved for each variable iteratively. The spacing of the computational grid affects the accuracy of the simulation. It is essential that the calculation grid is fine where the velocity gradients are steep while in areas with smaller gradients the grid may be more coarse. In practice, the grid-dependency of the numerical simulation should be studied by using grids of different density.

The boundary conditions have crucial effect on the results of the calculations. Therefore it is essential that the boundary conditions are realistic. Often the most

(8)

(9)

(10)

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important and difficult task in the numerical simulation is the assessment of reliable boundary conditions.

NUMERICAL CALCULATIONS

The air flow fields for different kinds of exhaust openings drawing air from still air were simulated numerically. The simulations were performed for two-dimensional plain and flanged slots, circular unflanged and flanged openings, and for three- dimensional unflanged and flanged rectangular openings. The circular openings were solved in cylindrical co-ordinates and the rectangular openings in three-dimensional Cartesian co-ordinates. The co-ordinate systems and computational domains for unflanged openings are shown in Fig. 1. The dimensions in the figure are inside widths or diameters of the exhaust ducts. The free-stream boundaries were sufficient distant to ensure that they did not significantly affect the air flow fields of the suction openings. In each case, the hood face was situated in the middle of the computational domain. In the two-dimensional case the air flow field was assumed symmetrical with respect to the x-axis. In the three-dimensional case xy and xz planes were planes of symmetry. Axial symmetry was assumed for the circular openings. The exhaust duct walls were parallel to the symmetry axes.

11 w

r--------- --------------

----------------------------------j n ------ -------~--l-----------

4D

8D

Two-dimensional slot Circular opening

10W

1 10W

Three-dimensional rectangular opening

Fig. i. Computational domains and co-ordinate systems for unflanged openings.

The time-averaged equations of turbulent flow were solved with the FLUENT version 3.02 computer code based on the finite model using the k-e turbulence model. Non-uniform grids were used with fine grid spacing near the hood face. The effect of the walls was calculated using wall functions.

The velocity distribution in the exhaust duct was assumed uniform and parallel to the exhaust duct walls at the boundary. The velocity in the exhaust channel was 10 m s ~1 in each case and the turbulence intensity was set to 10% of the mean velocity. A fixed pressure boundary condition was used at the free-stream boundaries. This is

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456 I. Kulmala

not quite valid, but because the calculated velocities at the free-stream boundaries were in all cases less than 3% of the mean face velocity, the effect of dynamic pressure on the results was negligible. The fixed pressure condition is also very easy to give as a boundary condition in the FLUENT computer program.

Sufficient convergence was assumed to be reached, when the sum of successive fractional changes (residuals) was less than 10~3. A typical solution for the two-dimensional velocity field using 2294 grid points required 12 min of CPU time and for the three-dimensional velocity field using 25 056 grid points required 930 min of CPU time on Sun Sparc Server 690 MP. The solution algorithm was a semi-implicit method for pressure linked equations (SIMPLE) and the differencing scheme was quadratic upstream interpolation for convective kinematics (QUICK) for three- dimensional cases and power-law for the other cases.

Plain slot

Slots can be thought of as rectangular unflanged hoods with a very large aspect ratio (the ratio of slot length L, to its width, W). The geometry and calculations domain of the two-dimensional slot are shown in Fig. 1. The dimensions of the calculation domain were 22 Win the x direction and 11 W in the y direction, where W is the width of the opening (0.1 m). The grid size was 62x37 points. At the hood face seven calculation cells were used in the y direction. The thickness of the exhaust duct was 5 mm and the distance from the duct wall to the nearest grid point was 2.4 mm.

The numerical calculations were compared to the analytical solution for the slot in the two-dimensional case, which can be obtained by conformal transformation (Streeter, 1948)

z = e"' + w+1. (11)

This equation cannot be used directly, and numerical methods are needed to compute the velocity components. The validity of this model was verified by Anastas and Hughes (1989) who measured velocities for a rectangular opening of aspect ratio 1:100 and found good agreement between the theoretical model and experimental values.

Figure 2 shows the numerically calculated velocity contours as a fraction of the average velocity in the channel (average face velocity). In the two-dimensional case, the velocity of constant velocity contours was calculated by

—Analytical solution — Numerical solution

0.4 0.2

j_____ 0 1 2 3 4

Distance (x/W)

Fig. 2. Velocity contours for plain slot by numerical and analytical methods. Numbers indicate fraction ofaverage face velocity.

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K=x/u2 + u2, (12)

where u and v are velocity components in the x and y directions, respectively. In addition, analytical solutions obtained by an iterative technique presented by Anastas and Hughes (1989) are plotted. It can be seen that compared to the analytical solution the numerically calculated contours were displaced somewhat in the positive x direction. The criteria for the distance of the nearest wall grid point is satisfied when the velocity is over 2.6 ms-1. For velocities less than 2.6 m s'"1 the adjacent grid point is too close to the wall for the logarithmic wall function to predict the shear stresses accurately. The strong bending of velocity contours near the wall for fractional velocities less than 0.2 may be due to this. On the other hand, the theoretical model assumes frictionless flow and the velocity near the surface is the same as outside the boundary layer.

The numerically calculated centre-line velocities are plotted with theoretical values as a function of dimensionless distance from the exhaust opening {x/W] in Fig. 3. The relative velocity is defined as F/ V0 where the average face velocity V0 = q/A. In the same figure the relative difference between analytically calculated and numerically calculated values at different grid points is also plotted: this is defined as

T^.„ .... Numerical solution —Analytical solution .nnDifference (%) =---------------- -———-— ------------------- x 100.

Analytical solution

Owing to the displacement of the numerically calculated velocity contours the relative difference is greatest near the exhaust opening and decreases as the dimensionless distance x/W increases.

-—Analytical solution

— Numerical solution

-^-Difference

20 C

10 It:

Distance (x/W)

Fig. 3. Predicted and theoretical centre-line velocities (left axis) and relative difference (right axis) in front ofplain slot.

Flanged slot

The numerical model for the flow into a flanged slot was the same as for the plain slot except for the wall in the positive y direction. The nearest point to the flange was 2.3 mm from the wall and this implies the smallest air velocity 2.7 ms-1 for which the wall shear stresses can be calculated accurately according to the criterion for the logarithmic wall function.

The analytical solution for an infinitely flanged slot can be obtained from the model developed by Tyaglo and Shepelev (1970) by setting the aspect ratio of a rectangular

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458 I. Kulmala

hood to infinity. The velocity components were calculated in the x direction using the equation

u(x, y)= ~~ n

arctany+fF/2

x— arctan

y-fF/2

and in the y direction using the equation

(13)

r(x, y) —------ In71(y+ Wj 2)2 + x2(y-fF/2)^ + x^

(14)

where V0 is the average hood face velocity, W is the width of the opening and x and y are the distances from the hood centre. The negative sign indicates that the flow is in negative x and y directions towards the hood face. The applicability of this model was verified by Anastas and Hughes (1989) and by Drkal (1971), who compared theoretical to experimental centre-line velocities and found close agreement.

The correspondence between numerically calculated velocity contours and the analytical model is generally good, as can be seen in Fig. 4. Near the wall disagreements are found for velocities less than lms-1 (under 10% of face velocity). The predicted centre-line velocities with analytical values are plotted in Fig. 5. The analytical centreline velocities were calculated from the equation

V 2— = - arctanV0 71

which is obtained from Equations (12), (13) and (14) by setting y = 0.

(15)

Analytical solution ------- Numerical solution

W 1 \ Distance (x/W)

Fig. 4. Velocity contours for flanged slot by numerical and analytical methods.

The numerically calculated centre-line velocities are in excellent agreement with the analytical model, as can be seen from Fig. 5. The numerical model slightly overestimates the analytically calculated centre-line velocity but the difference is less than 5%.

Plain circular opening

The numerical model used cylindrical co-ordinate system with the axis of the exhaust duct coinciding with the z-axis. An axial symmetry was assumed, which

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459Numerical calculation of air flow fields

10

0 o0 12 3 4

Distance (x/W)

Fig. 5. Predicted and theoretical centre-line velocities in front of plain slot.

reduced the problem to an equivalent two-dimensional problem. The inside diameter of the tube was taken to be 103.6 mm and the thickness of the wall was 3.2 mm. The exhaust flow rate was 0.079 m3s_1. The flow field was calculated for a region extending up to four tube diameters both in the positive z direction and r direction from the centre of the hood face (Fig. 1). The grid size was 78 x 50. Twelve grid points covered the suction opening. The distance of the adjacent grid node to the duct wall was 1.7 mm so that wall shear stresses for velocities over 3.7 ms'1 are predicted correctly according to the log law criteria.

An analytical solution has not been found for an unflanged circular hood. The calculated air velocity contours for unflanged circular openings were thus compared to DallaValle’s classic measurements (DallaValle, 1952) and are shown in Fig. 6.

Where the velocities were over 10% of the average face velocity the calculated contours remained close to the experimental values. At greater distances from the exhaust opening numerical calculations predict greater velocities than measurements. On the other hand, there is some discrepancy in the experimental values at greater distances from the hood face. If the area of surface generated by revolution of the measured 5%

equal air velocity contour about the symmetry axis is calculated, it may be seen that it is only about 15 times the area of the hood face. According to the mass conservation principle the area should be 20 times the area of the face. Calculated from the numerical simulations the same area was 19.9 times the face area.

The generally accepted empirical centre-line velocity equation for unflanged circular opening takes the form (DallaValle, 1952)

V _ 1T;~1 + 12.73(z/Z>)2’ (16)

where D is the diameter of the opening and z is the distance from the opening. Figure 7 shows the predicted centre-line velocity as a function of dimensionless distances (z/D), along with the values calculated from the empirically based equation. The greatest difference between experimental and numerically calculated centre-line values is about21%.

Flanged circular opening

The numerical model for the flanged circular opening was similar to the unflanged case except for the wall. The calculated values were compared to the solution presented

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460 I. Kulmala

----- DallaValle—— Numerical solution

- 0.5

0.8 0.4 0.2u i * -ii t i— D

Distance (z/D)

Fig. 6. Predicted and experimental velocity contours for unflanged circular opening.

.......DallaValle----- Numerical solution—e— Difference

Distance (z/D)

Fig. 7. Predicted and empirical centre-line velocities for unflanged circular opening.

by Drkal (1970). This solution has later been validated also by Flynn and Miller

(1988). In Drkal’s solution for an infinitely flanged circular opening with a radius of R

the velocity components are as follows

f/r, z)K<,r*r:" f(r+fcos%)2% Jo Jo (z' + r' + ^ + 2r(cosct)^ (17)

vr{r, z)= - Vo2n

h(z2 + r2 + l2 + 2rl cos a)3/2

da d/. (18)

The velocities were calculated by integrating Equations (17) and (18) numerically. For the centre-line Equation (18) yields along the z-axis (r = 0)

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vr'-jox+m*- <19)where D is the diameter of the opening and z distance from the opening. The numerically and analytically calculated velocity contours are shown in Fig. 8. One can see that the contours from both methods diverge slightly near the wall for relative velocities less than 0.2 ms"1 but the correspondence between the solutions is generally good. The numerically calculated and theoretical centre-line velocities are plotted in Fig. 9. A good agreement is confirmed also by the comparison of the centre-line velocities.

— - Analytical solution— Numerical solution

Distance (z/D)

Fig. 8. Velocity contours for flanged circular opening by numerical and analytical methods.

■------- Analytical solution

— Numerical solution

—e— Difference

. 0.6

Distance (z/D)

Fig. 9. Predicted and theoretical centre-line velocities in front of flanged circular opening.

Plain rectangular opening

The plain and flanged rectangular openings were modelled in the three-dimensional Cartesian co-ordinate system. The aspect ratio L/W of the opening modelled was 2:1 and the width W of the opening was 10 cm. At the hood face there were 5x10 grid

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462 I. Kulmala

points. The calculation domain was 20 W in the x direction and 10 W in the y and z directions (see Fig. 1). The flow field was assumed to be symmetrical with respect to the xy and xz planes and thus only a quarter of the flow field was calculated. The number of grid points was 36 x 24 x 29 = 25056. The number of calculation cells was thus approximately an order of magnitude greater than for two-dimensional cases and despite the simple geometry of the problem the simulations were much more complicated than in the two-dimensional case. Some difficulties were encountered during calculations of the flow field. Instead of using the power-law differencing scheme a QUICK algorithm had to be used to obtain converged solutions. The first grid point was 5.4 mm from the duct wall outside the channel. According to the criteria for the logarithmic wall function, for velocities over 1.2ms'1 the first grid is sufficiently remote from the wall to predict the wall shear stresses correctly.

There being no analytical solution for the plain rectangular opening, the numerically calculated results were compared to DallaValle’s experimental data (DallaValle, 1952). The predicted and measured velocity contours in symmetry planes are presented in Fig. 10. The velocities were calculated by

V = -Ju2 + v2 + w2, (20)

where u, v and w are velocity components in the x, y and z directions, respectively. Figure 10 indicates that the numerical calculations overestimate the velocities

0

Fig. 10. Predicted and experimental velocity contours in symmetry planes for unflanged rectangular openingwith aspect ratio 2:1.

compared to the measurements. Nevertheless, in all cases the same shapes of equal velocity contours are generated. Some of the difference may be due to the fact that Dalla Valle measured velocities for rectangular tapered hoods which were connected to a circular duct while the numerically simulated case concerns connections to a thick-

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walled rectangular duct. In the measurements conducted by DallaValle the exhaust opening probably drew more air from the region behind the opening.

The generally accepted experimental formula for the centre-line velocity in front of rectangular unhanged hoods is (Fletcher, 1977)

Fo 0.93 + 8.58%:'

where

% = and P = 0.2(x/^r^, (22)

W is the width and L the length of the opening and x is distance from the hood face. Figure 11 shows the numerically calculated centre-line velocities as a function of dimensionless distance from the hood face with an experimental formula. Numerically calculated results overestimate the experimental values by up to 26%. In the numerical model the thickness of the wall (1 cm) acts as a flange of small width. According to the measurements conducted by Fletcher (1978) it may be estimated that compared to a thin-walled duct the thickness of the wall increases velocities on the centre-line by approximately 1-4% at relative distances x/W 0.4-1.4.

Fig.

— Fletcher— Numerical solution

Difference 30

20

10

0

-10

-20

a>oc0)<1>

a

Distance (x/W)Predicted and empirical centre-line velocities for unflanged rectangular opening with aspect ratio

2:1.

Flanged rectangular opening

The numerical calculation grid size was 24 x 18 x 17 points. The size and shape of the hood face was the same as for the plain rectangular opening. At the hood face there were 5x10 grid points. The calculation domain was 8 IF in the x direction and 4 IF in the y and z directions. The distance between the flange wall and the first grid point was 4.4 mm and inside the duct 5.0 mm.

The numerical computations were compared to the analytical solution presented

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464 I. Kulmala

by Tyaglo and Shepelev (1970). In this model the velocity in the x direction is calculated using the co-ordinate system shown in Fig. 1

u(x, y, z) = K2n

arctan(>’ + fl)(z + h)

arctan

arctan

+ arctan

xx/(y + a)2 + (z + b)2 + x2

(y-a)(z + h)XsJ(y — a)2 + (z + b)2 + x2

(y + a){z-b)x^f(y + a)2 + (z-b)2 + x2

{y-a)(z-b)xy/{y^a)r+(z - b)2 + x2 _

and in the y direction

v(x, y,z)=- Vo2n

Inz + b + 'Jx2 + (y — a)2 + (z + b)2

_z + b + ^/x"2 + (y + a)2 + (z + b)2

z — b + y/x +(y + a) +(z-b)

z-b + y/x2 + {y~a)2 + {z-b)2

and in the z direction

(23)

(24)

Vo j [y + a + ^/x2 + (y + a)2 + (z-b)2

2n _y + ti + v/x2+"(jH-fl)2 + (z + h)2

y-a + y/x2 + (y-a)2 + (z + b)2~

y-a + y/x2 + {y~a)2 + (z-b)2_ ’(25)

where a = Lj2 is the half-length and b = W/2 is the half-width of the opening. Figure 12 shows that the numerically calculated velocity contours in symmetry planes are in good agreement with analytical solutions. The numerically calculated contours tend to be slightly flatter than the analytically calculated. At greater distances from the hood face the predicted velocities near the wall are lower than those of the analytical solution.

Along the hood centre-line (y = 0 and z = 0) the velocity components in the y and z directions disappear and the velocity can be calculated by

F 2 T1F— = - arctan----- 7—„—Fo % 2x^/4x2 + A2+lF2

(26)

Theoretically and numerically calculated centre-line velocities are in close agreement(Fig. 13).

CONCLUSIONS

The FLUENT CFD program was used to calculate the air flow fields of different kinds of local exhaust openings in an unobstructed isothermal condition. The calculated cases included two-dimensional plain and flanged slots, axisymmetric

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Fig. 12. Velocity contours in symmetry planes for flanged rectangular opening with aspect ratio 2:1 bynumerical and analytical methods.

• Analytical solution• Numerical solution

20

- 15

<D10 C 0)

0)

□

Fig. 13. Predicted and theoretical centre-line velocities in front of flanged rectangular opening with aspectratio 2:1.

plain and flanged circular openings, and three-dimensional plain and flanged rectangular openings. The accuracy of the simulations was examined by comparing the numerically calculated results with analytical solutions and experimental results.

The numerically predicted turbulent velocity fields correspond satisfactorily to the experimental results provided that the number of grid points is adequate and that the boundary conditions and boundary locations are appropriate. The agreement between the simulation and the potential flow theory was good in the case of the flanged

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466 I. Kulmala

openings. For the unflanged openings the predicted centre-line velocities tended to overestimate to some extent the theoretical (plain slot) or the.measured values (plain circular and rectangular opening) at distances which were of practical importance. However, the agreement with the measurements is satisfactory. The results become important when numerically modelling more complicated cases for local exhaust ventilation.

In two-dimensional cases the numerical calculations are quick, but the results have only limited practical use. In three-dimensional cases the restricting factor is the rapid increase in computational time as the size of the calculation grid increases. Computational fluid dynamics is a promising tool for turbulent flow calculation and its possibilities increase due to the rapid development of computer technology and CFD programs. The most difficult task in the numerical modelling will be to specify the reliable boundary conditions. Experimental measurements are still needed for specifying the boundary conditions for more complex cases of numerical simulation and for the validation of theoretical calculations.

Acknowledgements—The author would like to thank Mr Hannu Ahlsted of Tampere University of Technology for his help on the numerical calculations. This study was financially supported by the Technology Development Centre (TEKES).

REFERENCESAnastas, M. Y. (1991) Computation of the initially unknown boundaries of flow fields generated by local

exhaust hoods. Am. ind. Hyg. Ass. J. 52, 379-386.Anastas, M. Y. and Hughes, R. T. (1989) Finite difference methods for computation of flow into local

exhaust hoods. Am. ind. Hyg. Ass. J. 50, 526-534.Awbi, H. B. (1991) Ventilation of Buildings. Chapman & Hall, London.Braconnier, R., Regnier, R. and Bonthoux, F. (1991) Efficiency of an exhaust vent on a surface treatment

tank—Laboratory measurements and two-dimensional numerical simulation. Cah. Notes Doc. 144, ND1841, 463-478. (In French).

DallaValle, J. M. (1952) Exhaust Hoods (2nd Edn). Industrial Press, New York.Drkal, F. (1970) Stromungsverhiiltnisse bei runden Saugdffnungen mit Flansch. Z. Heiz. Liift. Klim. Haus.

21,271-273.Drkal, F. (1971) Theoretische Bestimmung der Stromungsverhiiltnisse bei Saugschlitzen. Z. Heiz. Liift.

Klim. Haus. 22, 167-172.Fletcher, B. (1977) Centreline velocity characteristics of rectangular unhanged hoods and slots under

suction. Ann. occup. Hyg. 20, 141-146.Fletcher, B. (1978) Effects of flanges on the velocity in front of exhaust ventilation hoods. Ann. occup. Hyg.

21, 265-269.Flynn, M. R. and Ellenbecker, M. J. (1985) The potential flow solution for air flow into a flanged circular

hood. Am. ind. Hyg. Ass. J. 46, 318-322.Flynn, M. R. and Ellenbecker, M. J. (1987) Empirical validation of theoretical velocity fields into flanged

circular hoods. Am. ind. Hyg. Ass. J. 48, 380-389.Flynn, M. R. and Fitzgerald, M. L. (1989) A comparison of three-dimensional velocity models for flanged

rectangular hoods. Appl. ind. Hyg. 4, 210-216.Flynn, M. R. and Miller, C. T. (1988) Comparison of models for flow through flanged and plain circular

hoods. Ann. occup. Hyg. 32, 373-384.Garrison, R. P. and Park, C. (1989) Evaluation of models for local exhaust velocity characteristics—Part

One: Velocity contours for freestanding and bounded inlets. Am. ind. Hyg. Ass. J. 50, 196-203.Garrison, R. P. and Wang, Y. (1987) Finite element application for velocity characteristics of local exhaust

inlets. Am. ind. Hyg. Ass. J. 48, 983-988.Heinsohn, R. J. and Choi, M. S. (1986) Advanced design methods in industrial ventilation. In Ventilation 85,

Proceedings of the First International Symposium on Ventilation for Contaminant Control (Edited by Goodfellow, H. D ), pp. 391-403. Elsevier Science, New York.

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Launder, B. E. and Spalding, D. B. (1974) The numerical computation of turbulent flows. Comput. Meth. Appl. Mech. Engng 3, 269-289.

Root, W. (1984) Turbulence Models and Their Applications in Hydraulics. International Association for Hydraulic Research, Delft.

Streeter, V. L. (1948) Fluid Dynamics. McGraw-Hill, New York.Tyaglo, I. G. and Shepelev, I. A. (1970) Dvizhenie vozdushnogo potoha k vytyazhnomu otverstiyu. [Air

flow near an exhaust opening.] Vodosnab. sanit Tekh. 5, 24-25.

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Reprinted with permission from the publisher.In: Staub - Reinhaltung der Luft 1995. Vol. 55, pp. 131 - 135.

Paper 2

Numerical calculation of an air flow field near an unflanged circular exhaust opening

I. Kulmala, P. Saarenrinne

Abstract Turbulent air flow fields for an unflanged circular opening were calculated numerically using the FLUENT computer code based on the finite volume method. The turbulence models used in the simulations were the standard two- equation k-e turbulence model and an algebraic stress model (ASM). The accuracy of the calculations was verified by experimental laser-Doppler anemometer velocity measurements and by comparison with previous measurements. The results show that the agreement between simulation and experiment was satisfactory with the k-e turbulence model and good with the ASM-model.

Numerische Berechnung des Strdmungsfeldes bei runden Saugrohren ohne FlanschZusammenfassung Es wurden turbulente Stromungsfelder fur ein rundes Saugrohr ohne Flansch mit dem FLUENT-FIuid- stromungsprogramm numerisch berechnet. Fur die Simulation wurde das k-e-Turbulenzmodell (Zwei-Gleichungs-Modell) und das algebraische Spannungsmodell verwendet. Versuche mit Laser-Doppler-Anemometer und der Vergleich mit friiheren Mefiergebnissen sicherten das Rechenergebnis ab. Das Resultat zeigt, dafi die mit dem k-e-Turbulenzmodell berechneten Ge- schwindigkeitswerte ausreichend mit den Experimenten iiber- einstimmen. Mit dem algebraischen Spannungsmodell war die Obereinstimmung gut.

List of symbolsC^,Csl,Ce2 empirical constants in the k-e turbulence model CD, C3 empirical constants in the algebraic stress turbu

lence modelD diameter of circular openingk turbulence kinetic energyP production of turbulence kinetic energyPij production of Reynolds stressesp mean pressurer radial coordinateU,V,W mean velocity components in r, z, 0 direction

v', w' fluctuating velocity components in r, z, d direction Vr magnitude of velocity at a pointU0 mean velocity at the hood facez axial coordinateSij Kronecker delta, 5^=1 for i=j and 0 otherwise£ turbulence dissipation rate6 tangential coordinatev kinematic viscosityv, turbulent viscosityp fluid densitycrk,ae turbulent Prandtl numbers

1IntroductionIn industry there are several situations where airborne contaminants are produced over a restricted area. In order to remove these contaminants close to their point of generation

and prevent them from entering into the workplace air local exhaust ventilation (LEV) systems are widely used. The transport of contaminants and thus the efficiency of the local exhaust is greatly affected by the air flow field induced by the exhaust hood. Therefore there has been a lot of research in recent years concerning air velocity fields generated by different kinds of exhaust openings. In potential flow solutions simplified models are obtained by assuming irrotational and inviscid flow, but the air flows encountered in practice are very often turbulent. Thanks to the advances in computer technology and computational fluid dynamics (CFD) programs these flows can now be solved numerically by using an appropriate turbulence model.

Traditionally the design of local exhaust ventilation hoods is based on the empirical centreline velocity formulas and on the capture velocity, which means the velocity in front of the hood necessary to capture the contaminants into the hood [i]. However, in order to calculate the contaminant transport more accurately, detailed knowledge about the flow field near the exhaust opening is needed. The early 1970 *s brought important analytical solutions based on potential flow theory concerning the flow into infinitely flanged exhaust openings; Tyaglo and Shepelev [2] presented a model for flanged rectangular openings, and Drkal obtained a model for a flanged circular [3] hood and for a flanged two-dimensional slot [4]. These models were later shown to be in good agreement with air velocity measurements [5, 6].

For unflanged rectangular or circular hoods analytical solutions have not been found. When the potential functions of the flow field are unknown, numerical methods are needed to solve the flow field. These unflanged exhaust openings have been modelled by the finite difference method [6, 7], by the finite element method [8] and by the boundary integral method [9].

Although the models based on potential flow solutions work well for unobstructed exhaust openings, they are inadequate when dealing with complex cases where turbulent stresses are significant. A case in point is, for example, wakes caused by obstacles in the flow field, plumes and recirculating flows. To simulate these flows, numerical methods are needed with a suitable turbulence model. Recent studies show that turbulent air flow fields near exhaust openings may be simulated numerically with reasonable accuracy [10,11]. The aim of this study was to compare two turbulence models when calculating an air flow field generated by an unflanged circular exhaust opening. The calculations were done using the standard k-e and the algebraic stress turbulence models (ASM) and the results were compared with the laser Doppler anemometer measurements.

2TheoryIn the numerical simulations, the Navier-Stokes equations describing air flow are time-averaged, which yields a set of

uV

w

Fig. l. The coordinate system

equations which describe the mean flow. Time-averaging causes additional unknowns, called the Reynolds stresses, to appear in the momentum equations, and they must be represented by a suitable turbulence model in order to solve the mean-flow equations. The most widely used two-equation turbulence model is the k-£ model but recently much research is also being done on the Reynolds stress models and the algebraic stress models (ASM).

In this study the air flow was assumed to be isothermal and incompressible. Under calm air conditions, axial symmetry could be assumed and therefore a cylindrical co-ordinate system was used with the axis of the exhaust duct coinciding with the z-axis (Figure 1). Due to the axial symmetry, the mean velocity W and all the changes in the tangential direction d can be neglected. The time-averaged steady-state equations governing turbulent air flow are thus the continuity equation

dU | 1 drV dz r dr

=0 (i)

and the momentum equations in the axial direction:

dz dr pdz \dz2 rdr\ dr))dtp2 1 dru'v' dz r dr

and in the radial direction:

rdvi dv i dp (d2v \ d ( dv\ ydz dr p dr \dz rdr\ dr) r2

duV 1 dr?2 v/2 dz r dr r

(2)

(3)

where U, V, u’and v'are the mean and fluctuating velocity components in the z and r directions, p is the mean pressure, v is the kinematic viscosity and p is the density. In Equation (3) w'is the fluctuating velocity component in the $ direction. In the k-e turbulence model the Reynolds stresses are expressed by mean strain rates:

Simplified formulas for the turbulent kinetic energy and the dissipation rate are calculated by:

dz dr dz\akdz) rdr\ cskdr) (6)

dz dr dz\aedz) rdr . crc dr,

(7)

where Cel und C.,., are model constants and ak and cre are the Prandtl numbers for k and £, respectively, and their values are C6]=i.44, C,;2==i.92, crk=i.o and cre=i.3. P is the production of turbulent kinetic energy expressed as:

In complex flows (e.g. highly buoyant or swirling flows, or flows with strong streamline curvature) the assumption that the eddy viscosity is the same for all Reynolds stresses may be too crude. When the turbulence is highly anisotropic more elaborate turbulence models should be used.

In an algebraic stress model (ASM) the exact transport equations for the Reynolds stresses are approximated. In the axial symmetric case these modelled stresses are simplified in the FLUENT code as:

^2---- (P'.—^S..pP—i+c3e£

3 " (9)

where the values of the constants used in these simulations were CD=o.55 and C3=2.2. The stress production ft of Reynolds stresses is

. — Vr

dz dr fdU V'

u’W |---- F— l + v’w’dz r) dr

dz \r dr

V dz dr dU

P=2(%r+S, + W (l0)

u,2=-2v•+~k' dz 3 +-t ' dr 3

— V 2w'2——2vt—+-k

r 3 (4)

where the turbulent kinetic energy k characterizes the intensity of turbulent fluctuations and vt is the turbulent viscosity, which is calculated from:

ve (5)

where e is the dissipation rate of turbulence. The empirical constant Cp has been determined on the basis of experimental data for simple boundary layer flows and its value has been found to be about 0.09.

The above equations were solved numerically with the FLUENT version 3.02 computer code based on the finite-volume method. The solution algorithm was a semi-implicit method for pressure linked equations (SIMPLE) and the power-law differencing scheme was used [12]. The effects of the duct walls were taken into consideration with the wall function method[13]-

The calculation domain and grid are shown in Figure 2.The numerical model used a cylindrical coordinate system with the axis of the exhaust duct coinciding with the z-axis. The flow field was calculated for a region extending up to four tube diameters both in the positive z-direction and r-direction from the centre of the hood face. The size of the non uniform grid was 70X58 with twelve grid points covering the suction opening. A uniform velocity was assumed in the ex-

2/2

10

7Fig. 2. The calculation domain and grid

haust duct (boundary 11) with a turbulence intensity of to%.A fixed pressure was assumed at the free-stream boundaries (boundary I o) and an axisymmetric boundary condition at the centre line of the exhaust duct (boundary 12). The tube inside diameter was taken to be 103.6 mm and the thickness of the wall was 3.2 mm. The exhaust flow rate was 0.084 m3/s corresponding to the mean bulk velocity of 10 m/s in the exhaust duct.

3MeasurementsThe air velocities were determined experimentally by laboratory measurements. In order to minimize the effects of ambient disturbances on the results, the measurements were conducted in a test room with a floor area of 4.8 01X3.6 m and volume of 62 m3. The exhaust hood was a circular PVC duct with dimensions similar to those used in the calculations, and it was suspended in the middle of the test room at a height of 1.2 m above the floor. During the measurements the supply air into the test room was introduced through a low-velocity outlet so that ambient air velocities around the exhaust opening were very small. The exhaust air flow rate through the hood was 0.084 m3/s and it was measured by using a standard ISA 1932 nozzle [14].

The set up of the measurement system is shown in Figure 3. The velocities were measured with a laser Doppler anemometer (LDA), which is a nonintrusive optical measurement method. It can detect the direction of the velocity and it is especially suitable for highly turbulent flows.

The velocities were measured by a one-dimensional fiber optical set up and a PDA processor (manufacturer DANTEC Meas. Tech.). The set up includes a 3 W Spectra Physics 164 Ar-Ion laser. The main optical parameters were: focal length of the front lens 400 mm, beam separation 38 mm, wavelength of light 514.5 nm. The dimensions of the measurement volume were: diameter 210 pan, length 4.4 mm, fringe separation 5.4 pm.

The flow field has to be artificially seeded by tiny particles. Both the particle mean diameter and particle distribution in the flow field are critical. The size has to be small enough to follow the movement of turbulent eddies in the flow field and bigger than the light wavelength to guarantee Mie-scattering from particles. In addition, the particle concentration should be as uniform as possible in the test room to prevent statistical biases.

The measurements used olive oil droplets generated with a TSI Six Jet atomizer for particle seeding. The seeding generator was placed far away from the exhaust opening, just downstream of the low velocity outlet of the supply air to ensure

Optical fibersExhaustopening Probe,

Flow in

Transmitter

Laserbeams Traversing

system

PhotomultiplierAr-Ion laser

Fig. 3. Measurement setup

uniform seeding inside the whole room. The mean diameter of the droplets was 0.6 pm, according to the manufacturer’s information.

The measurement procedure was started by carefully aligning the traversing system with the symmetry axis of the exhaust opening. Velocities were measured in the r-z-plane at 11X28 different locations in front of the exhaust hood. First, the velocity in the axial direction was measured at each point. Then the probe was rotated 90° around its symmetry axis and the velocities in the radial direction were measured. 3000 samples were collected at each point. The results were fed into a microcomputer. Instantaneous velocity time series and other statistical quantities were calculated by the microcomputer, which also automatically traversed the probe through predetermined coordinate points. From the measured autocorrelations, estimated time macroscales were of the order of 3 ms.To ensure a statistically independent sampling procedure a dead time of 2 ms was used between samples.

4ResultsThe calculated and the smoothed representations of the measured velocities are shown in Figure 4 and a comparison between centreline velocities in Figure 5. The velocities in Figure 4 are presented as constant velocity contours and they were calculated from axial and radial velocities by:

V = VU2+V2 (11)

and they are expressed as a percentage of the average face velocity. The upper part of the figure shows the calculated velocities based on the ASM and in the lower part the k-e predictions are plotted. In addition, the widely quoted contours obtained by Dalla Valle are presented [15]. Where the velocities were in the range from 10 to 50% of the face velocity, the k-e model predicts somewhat greater velocities than the LDA- measurements, but the overall agreement is satisfactory. On the other hand, the results obtained with the ASM are very close to the LDA-measurements for all the measured velocity ranges. Dalla Valle’s results correspond quite well to the LDA- measurements for velocities greater than 10% of the face velocity.

The comparison of the predicted and the measured centreline velocities as a function of dimensionless distance from the exhaust opening is displayed in Figure 5. The figure also shows the generally accepted empirical equation for the centreline velocity in front of an unflanged circular hood [15]

[7„ 1 + 12.73 (z/D)2

2/3

Measured

80 50 30 20

Dalla Vallek - e model

Fig. 4. Empirical, predicted and experimental constant velocity contours

----- Dalla Valle------k - e model

..... ASM° Measured.

0.1 r

=3 0.4

z/D 2

Z/D

Fig. 5. Empirical, predicted and experimental centreline velocities

where U is the centreline velocity at the distance z from the exhaust opening, D is the duct diameter and U0 is the mean hood face velocity. It can be seen that the numerical calculations agree fairly well both with the experimental data and with the empirical equation. The k-e model overestimates the measured centreline velocities at maximum by io%, whereas the ASM overestimates them at maximum by 4%.

5DiscussionThe air flow fields into an unflanged circular opening were calculated numerically using two different turbulence models and the results were verified by experimental measurements with laser Doppler anemometer, which gives accurate velocity readings without disturbing the measured air flow. When the power law differencing scheme was used, the air flow fields could be predicted with satisfactory accuracy by the k-e turbulence model. With the ASM the agreement between prediction and measurement was good. Nevertheless, the ASM may require more calculation time than the k-e model because of the increase in the number of solved equations. In this study

the CPU time per iteration with the ASM was 4.1 seconds, whereas with the k-e model it was 3.4 seconds on a Sun Spark Server 690 MP. However, due to faster convergence, the ASM calculations required only 304 iterations, whereas the k-s calculations needed 499 iterations for convergence, so that the total calculation time was shorter when the ASM was used.

The measured and calculated constant velocity contours are in substantial agreement with those of DallaValle for velocities greater than 10% of the mean face velocity. At greater distances from the exhaust opening numerical calculations and LDA measurements give greater velocities than Dalla Valle’s measurements. The discrepancies in Dalla Vella’s measurements may be ascertained by calculating the area of the surface which is generated by revolution of the measured 5% constant velocity contour about the symmetry axis. This area is about 15 times the area of the hood face whereas according to the mass conservation principle it should be 20 times the area of the face. One possible explanation is that in his measurements DallaValle used a modified pitot tube with which it is difficult to measure low air velocities accurately.

The differences between the two turbulence models for practical purposes were not great. In addition, the results are quite close to Flynn and Miller’s predictions based on potential flow theory [6]; Therefore it may be concluded that the turbulent stresses do not have very great effects on the flow into unobstructed exhaust openings, except very close to the hood face. However, in industrial applications there are often obstacles in the exhaust air flow field and the contaminants have a momentum which cannot be neglected (e.g. welding fumes). It is likely that in these cases the models based on potential flow theory do not perform satisfactorily and for more accurate modelling the effects of turbulence must be taken into consideration. Moreover, nearby surfaces or crossdraughts may destroy the axial symmetry and solutions must be obtained using three-dimensional models, which requires considerably more computer time.

The standard k-e model is currently the most widely used turbulence model in practical air flow simulations. In cases where strong anisotropy in turbulence exists it is to be expected that models that are based on the transport equations for each individual Reynolds stress component would perform better. Such cases are, for example, flows with strong external forces. However, the accuracy of the simulations does not depend on the turbulence model alone; boundary conditions and locations, calculation grid and differencing schemes may greatly effect the results. Further research is needed to determine the applicability and limitations of numerical models in order to simulate local ventilation under more realistic conditions.

Acknowledgements This study was a part of the industrial ventilation (INVENT) technology programme, financially supported by the Finnish Technology Developement Centre (TEKES). The assistance of Mr. Jouni Uusitalo on the experimental measurements is gratefully acknowledged.

References1. American Conference of Governmental Industrial Hygienists, Com

mittee on Industrial Ventilation: Industrial ventilation - a manual of recommended practice. 19th ed. Cincinnati: American Conference of Governmental Industrial Hygienists 1986

2. Tyaglo, LG.; Shepelev, LA.: Dvizhenie vozdushnogo potoha k vytyazhnomu otverstiyu (Air Flow near an Exhaust Opening). Vodosnab. sanit. Tekh. 5 (1970), pp. 24-25

3. Drkal, F.: Strdmungsverhaltnisse bei runden Saugoffnungen mit Flansch. Z. Heiz. Liift. Klim. Haus. 21 (1970) No. 8, pp. 271-273

4. Drkal, E: Theoretische Bestimmung der Strdmungsverhaltnisse bei Saugschlitzen. Z. Heiz. Liift. Klim. Haus. 22 (1971) No. 5, pp. 167-172

2/4

5. Flynn, M.R.; Fitzgerald, M.L.: A comparison of three-dimensional velocity models for flanged rectangular hoods. Appl. Ind. Hyg. 4

(1989) No. 8, pp. 210-2166. Flynn, M.R.; Miller, GT.: Comparison of models for flow through

flanged and plain circular hoods. Ann. occupat. Hyg. 32 (1988)No. 3, pp. 373-384

7. Anastas, M.Y.; Hughes, R.T.: Finite difference methods for computation of flow into local exhaust hoods. Amer. Ind. Hyg. Assoc. J. 50

(1989) No. 10, pp. 526-5348. Garrison, R.P.; Wang, Y.: Finite element application for velocity

characteristics of local exhaust inlets. Amer. Ind. Hyg. Assoc. ]. 48

(1987) No. 12, pp. 983-9889. Flynn, M.R.; Miller, C.T.: The boundary integral equation method

(BIEM) for modeling local exhaust hood flow fields. Amer. Ind. Hyg. Assoc. J. 50 (1989) No. 5, pp. 281-288

10. Scholer, W.: Ausiegung von Einrichtungen zur Schadstofferfassung. Z. Heiz. Ltift. Klim. Haus. (1993) No. 8, pp. 506-507

11. Kulmala, I.: Numerical calculation of air flow fields generated by exhaust openings. Ann. occupat. Hyg. 37 (1993) No. 5, pp. 451-467

12. Patankar, S.V.: Numerical heat transfer and fluid flow. Washington, DC: Hemisphere 1980

13. Launder, B.E.; Spalding, D.B.: The numerical computation of turbulent flows. Comput. Meth. Appl. Mech. Engng. 3 (1974), pp. 269-289

14. ISO 5167-1980: Measurement of fluid flow by means of orifice plates, nozzles and venturi tubes inserted in circular cross-section conduits running full 1980

15. DallaValle, J.M.: Exhaust hoods. 2nd ed. New York: Industrial Press 1952

Reprinted with permission from the publisher.In: American Industrial Hygiene Association Journal 1995. Vol. 56, November, pp. 1099 - 1106.

Paper 3

AuthorUpo Kulmala

Tampere University of Technology, Thermal Engineering, P.O. Box 589, 33101 Tampere, Finland; On leave from Technical Research Centre of Finland, Manufacturing Technology, P.O. Box 1701, 33101 Tampere, Finland

Numerical Simulation of Unflanged Rectangular Exhaust Openings

Local exhaust hoods are commonly used for controlling airborne contaminants in industry.The transportation of the contaminants is mainly affected by air movements, and therefore it is important to know the flow fields near exhaust openings accurately. Recent developments in computer technology and in computational fluid dynamics programs have made it possible to simulate turbulent air flows into exhaust openings. However, the accuracy of the simulations is usually unknown. In this study isothermal three-dimensional airflow fields generated by rectangular exhaust openings with aspect ratios 1:1,4:3,2:1, and 3:1 were calculated numerically with the FLUENT computer code based on the finite volume method using the standard k-e turbulence model.The effect of free-stream boundaries on the simulations was studied by solving the airflow fields with different sizes of calculation domains.The accuracy of the predictions was determined by comparing the predicted results with the measured equal velocity contours and centerline velocities.The agreement between the numerical simulations and the experiments was good for openings with aspect ratios 1:1 and 4:3 and satisfactory for the other when fixed pressure boundary conditions on the free-stream boundaries were used. However, the location of the free-stream boundaries must be properly chosen. With a mean hood face velocity of 10 m/sec (1970 ft/min),an appropriate distance between the exhaust opening and the free- stream boundary was found to be 4A1", where A is the area of the exhaust opening.

Local exhaust ventilation (LEV) is widely used in industry for controlling airborne contaminants. A properly designed LEV system is an effective way of removing contaminants at the point of generation. Because the

transportation of the contaminants is mainly affected by air movements, a detailed understanding of the flow field generated by exhaust openings is important in designing an effective contaminant control. However, the equations describing turbulent airflows near exhaust openings are complex and cannot be solved analytically. Hence, the present design practices for local ventilation systems are based mainly on empirical equations and do not provide deeper insight into the underlying physical phenomena.

In recent years there has been much research on potential flow models in LEV. In this case, the flow is idealized by assuming it to be inviscid and irrotational, which greatly simplifies the mathematical treatment of flow cases. The first analytical model for an infinitely flanged rectangular opening was derived by Tyaglo and Shepelev,11’ and an analytical model for a flanged circular opening was derived by Drkal.(2) A model for the

circular opening in cylindrical coordinates also was presented by Flynn and Ellenbecker.(s-4) Except for the two-dimensional slot, no analytical solutions were found in the literature for unflanged openings. It is likely that numerical techniques are needed to solve the flow field.

Exhaust openings have been modeled by the finite difference method15-71 and by the finite element method.*81 Flynn and Miller191 used the boundary integral equation method for calculating the three-dimensional airflow field into flanged and unflanged rectangular openings. In most cases, the reported agreement between theoretical models and experimental values was good.

Although the potential flow solutions approximate the unobstructed flow field near exhaust openings quite well, they have inherent limitations. They are unable to describe common situations where turbulent stresses are significant, such as the wakes behind obstacles, jets, plumes, and recirculating flows. More realistic models can be obtained if the equations simulating the fluid flow are solved numerically along with the additional differential equations that describe the

effects of the turbulence on the mean airflow. Recently, this has become possible because of the developments in computer technology and in computational fluid dynamics (CFD) programs.

During the past two decades, there have been many studies on modeling turbulent airflows by numerical methods. However, not much research has been done on the viability of CFD for modeling flows into local ventilation hoods. Heinsohn and Choi"01 predicted two-dimensional turbulent velocity and contaminant concentration fields for a push-pull ventilation system, using Schlieren photographs to evaluate the validity of the calculations. Later, Braconnier et al."11 studied numerically the effects of cross-draft on the capture efficiency for an exhaust system of a surface treatment tank, and the results were verified by velocity and tracer gas measurements. Kulmala'12' calculated the airflow fields near unflanged and flanged exhaust openings and found a satisfactory agreement between the calculated and the experimental values. Scholer"3’ studied the effect of flanges and streamlining of the inlet opening on the velocities generated by a flanged circular hood. Recently, Ingham1141 solved the airflow field of an Aaberg exhaust system, which uses a jet to improve the capture efficiency of a slot hood. He found good agreement between a mathematical model, numerically calculated velocities, and experimentally observed velocities. In another study, the capture efficiency of an unflanged circular hood was determined numerically using a stochastic particle tracking technique."3' These calculations were verified by tracer gas measurements, and good agreement was obtained. In a recent study, the importance of reliable boundary conditions for accurate predictions was demon strated when modeling a local ventilation unit equipped with local supply and exhaust ventilation."6'

Although numerical simulations are promising, numerical solving of local ventilation problems is still at an early stage of development, and no clear guidelines exist on grid sizes, appropriate boundary conditions, or boundary locations. The aim of this study is to investigate the accuracy of the three-dimensional numerical simulations of LEV. The airflow fields were calculated for unobstructed unflanged rectangular exhaust openings with aspect ratios of 1:1, 4:3, 2:1, and 3:1. The results were compared with experimental results published in the literature. The effect of boundary locations on the results was also studied.

NUMERICAL SIMULATIONS

The time-averaged steady-state equations of continuity and momentum with turbulence energy and dissipation rate were solved with the FLUENT (version 3.02) computer code, which

is based on the finite volume method. Air was considered as an incompressible Newtonian fluid. Turbulence was modeled with the standard k-e two-equation model, using logarithmic wall functions near the duct walls as surface boundary conditions."7'

The time-averaged continuity and momentum equations for the isothermal flow using tensor notation are

where u, is the mean velocity component in the direction x, , p is the mean pressure, p is the dynamic viscosity, and p is the fluid

density. The last term on the right side of Equation 2 can be regarded as a gradient of extra apparent stress resulting from the transfer of momentum due to velocity fluctuations. These additional stresses are known as the Reynolds stresses, and, except in the viscous sublayers close to solid surfaces, they usually are much larger than the viscous stresses. The time-averaged equations can be solved numerically if these stresses can be related to the mean flow quantities. If an isotropic turbulence is assumed, the Reynolds stresses are thus approximated by

-pu,u; = p, dXj (3)

in which 6,j is th e Kronecker delta and k is the kinetic energy of turbulence defined as

k = X uju(4j

In the commonly used k-e model, it is assumed that at a high Reynolds number the local turbulent viscosity, p,, is related to the kinetic energy of turbulence k and the dissipation rate of kinetic energy, e, by the equation"7’

14 = C„p j, (5)

where is a constant (usually CM = 0.09). When determining an isothermal flow field, the following transport equations for k and e must be solved with the continuity and momentum equations:

Equation 8 represents the production rate of turbulence kinetic energy by the interaction of mean velocity gradients and turbulent stresses. The empirical constants appearing in the equations above usually have values ot = 1.0, oE = 1.3, C, = 1.44, and C2 = 1.92.

In numerical simulations, the calculation domain is divided into a number of grid points, and the differential equations are converted into a system of algebraic equations by discretization. A common discretization procedure in CFD is the finite volume method. The algebraic equations are solved iteratively for each variable at discrete spatial grid points. The spacing of the computational grid affects the accuracy of the simulation. It is essential that the calculation grid is finer where the velocity gradients are steep. In areas with smaller gradients, the grid may be more coarse. However, the maximum number of grid points is limited, and the computational time increases rapidly as the grid size gets bigger. In practice, the grid dependency of the numerical simulation should be examined by using a finer grid.

In this study, the power law differencing scheme was used for the discretization of the convection terms and the solution algorithm was the “semi-implicit method for pressure linked

3/2

1„, = 0.02A1/2. (11)

FIGURE 1. Calculation grid for exhaust opening with aspect ratio 12. X is the length, Y the height,and Z the depth ofthecalculationdomain.Listhe length and W the width of the exhaust opening.

equations.”1181 Sufficient convergence was assumed to have occurred when the sum of successive fractional changes (residuals) was CIO"3. Compared with a previous study021 in which a quadratic upstream interpolation for convective kinematics differencing scheme was used, no significant differences in the results were noticed. An example of a computational grid for a rectangular opening with the aspect ratio 2:1 is shown in Figure 1. A nonuniform grid was used, with a finer grid spacing near the exhaust opening. The flow field was assumed to be symmetrical with respect to the xy and xz planes, and thus only a quarter of the flow field was calculated. The exhaust opening was situated in the middle of the computational domain in the x direction. The thickness of the exhaust duct was either 5 mm (0.2 in.) or 10 mm (0.4 in.). The calculations were performed with cartesian grids, where grid lines run through the entire flow domain. Therefore, further grid refinements near the exhaust duct would extend into the free-stream boundaries where a fine resolution is not needed. Thinner ducts would also have resulted in cells with undesirable large aspect ratios near the free-stream boundaries (Figure 1).

To obtain the correct exhaust airflow, a uniform velocity profile parallel to the duct walls was assumed at the exit boundary. In reality, the flow would develop along the duct and the velocity would not be constant, but because the partial differential equations describing the flow inside the duct are parabolic, significant influences travel only from upstream to downstream. The conditions at the exhaust opening therefore are affected very little by the downstream conditions. This was also confirmed by calculations, in which the airflow field was calculated using both uniform velocity and with constant pressure at the exit boundary of a rectangular duct with the aspect ratio 2:1. The maximum difference between the two calculated centerline velocities in front of the exhaust opening was 0.5 %, when the distance was 0 < x < 3A1/2.

At the exit boundary the velocity, V0, inside the duct was 10 m/sec (1970 ft/min) and the turbulence kinetic energy was estimated by

k = 0.015Vo2, <9>

which corresponds to 10% level of turbulent intensity at the exit boundary. The exit value of £ was estimated from a length scale assumption

L (10)

where the mixing length lm was calculated by

At the duct walls, the no-slip condition applies, so that the mean velocity components are zero. Near the walls, the damping effect of the walls on the transport equations was calculated using the wall function method.02) In this method, the logarithmic law of the wall relation for velocity is used to patch the region of flow lying between the wall and the first calculation point adjacent to the wall:

where

u

u, = Vtw/p.

(12)

(13)

tw is the shear stress on the wall, k is the von Karman’s constant, E is a roughness parameter, and yP is the distance of the first calculation point from the wall. The equation for the turbulent kinetic energy, kP, is solved in the control volume immediately adjacent to the wall. From this value the wall shear stress is obtained

t„. = pkrc;/2

The boundary condition for the dissipation rate er is°9)

e cpw2

(14)

(15)

At the xy symmetry plane, the normal velocity component and the normal derivatives of all other variables are zero:

dkdz = 0, de

dz = 0, ^ =0.dz

(16)

The behavior is similar at the xz symmetry plane.At the free-stream boundaries, the velocity components, pres

sure, k, and £, are unknown. They also are very difficult to determine accurately. To circumvent the need to determine these variables, a fixed pressure boundary condition was used and the inlet turbulence and dissipation were set to zero at the free-stream boundaries. The fixed pressure boundary condition allows the user to input the total pressure at a boundary instead of defining the flow velocity. FLUENT can then compute the normal velocity component and the static pressure at the boundary by applying Bernoulli’s equation. This may lead to errors in the velocities if the boundaries are too close to the exhaust opening. However, if the free-stream boundaries are far enough from the exhaust opening, the velocities at the boundaries are small and it is likely that the calculated velocities near the exhaust opening are reasonably accurate.

To examine the influence of the free-stream boundary locations on the calculations, the flow field was solved for several sizes of the calculation domain. The size of the calculation domain was changed so that the ratio of the length of the domain to the height and depth remained the same (X = 2Y = 2Z in Figure I). Thus, when the calculation domain was expanded, the length of the exhaust duct was increased. The predicted centerline velocities

3/3

FIGURE 2. Predicted constant velocity contours in the symmetry plane for a square opening with different grid sizes. The contours correspond to relative velocities V/V, of 0.5,0.3,0.1, and 0.05, where V is calculated by Equation 19 and V, is the average face velocity.

were compared with the generally accepted1201 Fletcher’s1211 empirical model

V = 1V„ 0.93 + 8.58a2 (17)

where

solution was obtained. Similar considerations also were conducted for the other openings.

The final computational domains and grid sizes, together with the computational times on a Sun Spark Server 690 M, are presented in Table I. During the iterative solution procedure, rapid changes in the calculated variables should be avoided to promote stability. An underrelaxation restricts these changes in a variable to a fraction of the computed change. Increase of the underrelaxation during the calculations may result in a significant reduction in the number of iterations needed for convergence and thereby in the calculation times. However, during these calculations, no attempt was made to optimize the underrelaxation parameters to yield optimum convergence. In each case, the width of the opening was 10 cm (3.94 in.) and the thickness of the duct wall was 5

RESULTS

The effect of the free-stream boundary on the simulations is shown in Figure 3. The calculated constant velocity contours in the symmetry planes, and the comparison of numerically

predicted and curve fitted centerline values are presented in Figures 4-11.

In Figure 3 the relative difference of the centerline velocities between the numerically calculated and the curve fitted values is plotted for different calculation domains. The relative difference is defined as

Difference (%)Numerical solution — Curve fitted value

—----------------- —-------------- ;—:--------------------- X IUU.Curve fitted value

a = (x/Va)(L/Wf and P = 0.2(x/Va)"1/3. (18)

W is the width, L is the length of the opening, and x is the distance from the hood face. Fletcher measured the velocities with a constant-temperature hot-wire anemometer. He stated that the formula was accurate to within 5% of the true value in the range 0.05 < x/Al/2 < 3. On the basis of the comparisons between the predicted centerline velocities and Fletcher’s equation, the locations of the free-stream boundaries were selected to be sufficiently distant from the exhaust opening that they would not influence the computational results. For the average face velocity of 10 m/sec (1970 ff/min), an appropriate distance between the exhaust opening and the free-stream boundary (X/2 in Figure 1) is 4A1/2, where A is the area of the exhaust opening. In each case, Y = Z = X/2. An increase in this distance produced <3% differences in the calculated centerline velocities.

The effect of the grid size on the accuracy of the simulations was studied by calculating the airflow fields with different grid densities. An example of these calculations is shown in Figure 2, where the velocity contours for a square hood are presented in a symmetry plane. In these exercises, the size of the calculation domain was 8W X 4W X 4W (X X Y X Z). Because no detailed experimental data were available, the number of required grid points was deduced from the calculation results. For example, when the grid size was increased from 11,200 points to 19,584 points, the shape and the location of the constant velocity contours changed very little; the intersection points of the constant velocity contours and the hood centerline changed <1% on average (Figure 2). Thus, it may be assumed that a grid-independent

In each case the height Y and the depth Z of the calculation domain were equal to X/2, where X is the length of the domain. Close to the exhaust openings, the influence of the boundary locations was insignificant. Near the boundary of the calculation domain, the predicted velocities were clearly higher than the experimental values.

The calculations were performed with two wall thicknesses (s = 5 mm [0.4 in.] or s = 10 mm [0.8 in.]). The smaller thickness of the wall produces centerline velocities that are at maximum about 4% lower than with the greater thickness. The smaller duct thickness produced also a slightly better accuracy. Assuming linear relationship with duct thickness and centerline velocities, it can therefore be estimated that for thin-walled ducts the centerline velocities would be only a few percent smaller than the velocities presented in Figures 5, 7, 9, and 11. The results shown in the Figure 3 are for a square opening, but similar results were observed for the other rectangular openings.

Figures 4, 6, 8, and 10 provide comparisons between the

[TABLE I.Used for Simulations

ExhaustOpening

CalculationDomain

(X x Y x Z)Grid Size

(N, x N, x NJ

CPUTime(min)

1:1 8W X 4W X 4W 34 X 24 X 24 = 19 584 4594:3 10WX5WX5W 30X25X26 = 19500 5172:1 12W X 6W X 6W 36 X 27 X 25 = 24300 5673:1 14W X 7W X 7W 36 X 29 X 27 = 28 188 657

3/4

x//a

e X = 3W s/W=0.1 a X = 8W s/W=0.1■ X = 4W s/W=0.1 O X=1 OW s/W=0.1a X = 6W s/W=0.1 A X = 8W s/W=0.05

FIGURE 3. Relative differences between predicted and empirical centerline velocities for square opening with Afferent calculation domain sizes. The empirical velocity is calculated by Equation 17. X is the length of the calculation domain, W the width of the exhaust opening, and s is the duct wall thickness. A is the area of the exhaust opening and x is the distance from the hood face.

— Fletcher © Numerical solution

-a- Difference

30

20

10

0

-10

-20

o

FIGURE 5. Predicted and empirical centerline velocities (left axis) and relative difference (right axis) for unflanged rectangular opening with aspect ratio 1:1. V is the centerline velocity and Ve is the average face velocity. A is the area of the exhaust opening and x is the distance from the hood face.

V = i/u2 + v2 + w-, (19)

numerically predicted and Dalla Valle’s experimental velocity con-tours><22) which he obtained experimentally using a modified pitot tube, where u, v, and w are velocity components in the x, y, and z di- The magnitude of the constant velocity contours was calculated by rections, respectively. The correspondence between the pre

dicted and the measured velocity contours was reasonable in

FIGURE 4. Predicted and experimental constant velocity contours in symmetry planes for unflanged rectangular opening with aspect ratio 1:1. W is the width of the exhaust opening.

FIGURE 6. Predicted and experimental velocity contours in symmetry planes for unflanged rectangular opening with aspect ratio 4:3. W is the width of the exhaust opening.

3/5

— Fletcher © Numericol solution

-a- Difference

FIGURE 7. Predicted and empirical centerfine velocities for unflanged rectangular opening with aspect ratio 4:3.Vis the centerfine velocity and V0 is the average face velocity. A is the area of the exhaust opening and x b the distance from the hood face.

— Fletcher © Numericol solution

-A- Difference

x//A

FIGURE 9-Predicted and empirical centerfine velocities for imflanged rectangular opening with aspect ratio 2:1. V is the centerfine velocity and V, fa the average face velocity. A is the area of the exhaust opening and xb the distance from the hood face.

most cases. Except in the immediate vicinity of the exhaust opening (about x < 0.3A1/2), the predicted velocity contours tended to situate further from the opening than did the measured contours. For the square opening, the agreement was good for all but the 5% velocity contour, for which the experimental contour clearly was closer to the opening than the predicted one (Figure 4). On the other hand, Fletcher’s equation predicts that the 5% centerline velocity for a square opening would be located at x = 1.49 W, which is almost precisely where the numerically predicted contour intersects the centerline. For


the opening with the aspect ratio 4:3, the agreement also was good (Figure 6), but for the opening with the aspect ratio 2:1, the numerical calculations usually overestimated the velocities (Figure 8). As shown in Figure 10, the contours agreed well for the opening that had the aspect ratio of 3:1 in the xy plane. However, predictions overestimated velocities in the xz plane.

Nevertheless, in all cases above, the shapes of the numerically predicted equal velocity contours were the same as the experimentally obtained ones. Furthermore, some of the differences may be due to the fact that Dalla Valle measured velocities for rectangular tapered hoods that were connected to a thin-walled


3/6

— Fletcher © Numerical solution

Difference

0.8

>- 0 6 > 0,

0.2

00 0.5 1 1.5 2 2.5 3

x/v/A

FKUM11. Predicted and empirical centerline velocities for unflanged rectangular opening with aspect ratio 3:1. V is the centerline velocity and V, is the average face velocity. A is the area of the exhaust opening and x is the distance from the hood face.

circular duct, whereas the numerically simulated cases assumed thick-walled rectangular ducts. In Dalla Valle’s measurements, the exhaust hood probably drew more air from behind the opening than one would expect for a thick-walled or flanged opening.

Figures 5, 7, 9, and 11 show the numerically calculated centerline velocities as a function of dimensionless distance from the hood face along with velocities computed from Fletcher’s formula. The numerical predictions underestimated the centerline velocities close to the exhaust opening and overestimated the velocities at greater distances. This is consistent with the findings for the velocity contours. It is interesting that the maximum difference between the numerical simulations and the empirical values was located approximately at the same dimensionless distance x/Al/2 = 1 from the exhaust opening for each case. The maximum difference at that point seems to increase as the aspect ratio increases, and it ranges from 3% for the square opening to 29% for the opening with the aspect ratio 3:1 (Figures 5, 7, 9, and 11). However, the overall agreement between the experimental and the numerical centerline velocities is satisfactory for the rectangular openings and good for the square opening.

DISCUSSION

The k-e turbulence model can be used to predict the flow into exhaust openings with reasonable accuracy if boundary condi

tions and locations, calculation grids, and other modeling parameters are chosen correctly. The major weakness of the standard k-e model is the assumption of the isotropic turbulence. When the anisotropy of turbulence increases, the k-e model loses its ability to predict the flow field and second-order turbulence models, such as the Reynolds stress model (RSM) or the algebraic stress model (ASM), are needed. These models, however, require solution of more equations and therefore required unpractically long computational times for the computer used in this study.

Thus, it is not known whether the deviations between the numerically predicted and the experimental velocities are due to the differences in the exhaust hood geometry or to deficiencies of the

k-e turbulence model. The assumption of isotropic turbulence may be too crude for regions where air enters from behind the exhaust opening and turns into the duct abruptly. Additional fluid dynamics studies with different turbulence models (RSM, ASM) would be useful to investigate this. In this study, the use of such models was not possible because of the limitations of computer resources. A more rigorous validation of the numerical simulations would require velocity measurements for rectangular ducts with methods that do not disturb the velocity field, such as laser Doppler anemometry.

The choice of ffee-stream boundary did not affect the accuracy of the velocities near the exhaust opening when a fixed pressure boundary condition was used, although close to the ffee-stream boundary the centerline velocities were overestimated. However, when the computational domain is large enough, the velocities generated by exhaust openings close to the ffee-stream boundary are small, and these differences will result only in small absolute errors. With the mean face velocity of 10 m/s (1970 fpm), a reasonable distance between the exhaust opening and the ffee-stream boundary was found to be about x/A1/2 = 4, where A is the area of the exhaust opening.

Computational fluid dynamics has great potential for modeling local ventilation, and its possibilities increase continuously because of the rapid improvements in computer memory capacities and speeds together with the increasing sophistication of CFD programs. However, the accuracy of the simulations is greatly affected by the simplifications necessarily used in the simulations, including the modeling parameters and the boundary conditions. More research is needed to assess the feasibility of the CFD for design purposes.

ACKNOWLEDGMENTS

This study was a part of the industrial ventilation (INVENT) technology program, financially supported by the Finnish Technology Development Centre (TERES). The help of Dr. Hannu

Ahlstedt of Tampere University of Technology on the numerical calculations and of Mrs. Pirjo Turunen with the figures is gratefully acknowledged.

NOMENCLATUREAc„ c,, q,EGklmLPU;u:

U, V,w sVV0w%,y,zXY Z

area of exhaust openingempirical constants in the k-e turbulence model friction parameter in logarithmic law production rate of turbulent kinetic energy turbulence kinetic energy mixing lengthlength of rectangular opening mean pressuremean velocity component in direction xt fluctuating component of velocity component in di

rection Xjvelocity components in x, y, z directions thickness of duct wall magnitude of velocity at a point mean velocity at the hood face width of rectangular opening Cartesian coordinates length of calculation domain height of calculation domain depth of calculation domain

3/7

x, Cartesian coordinates in tensor notationSjj Kronecker delta, 5;j = 1 for i = j and 0 otherwiseE turbulence dissipation ratek von Karman’s constant, 0.42p dynamic viscocityp, turbulent viscosityp fluid densityok, aE empirical constants in the k-e turbulence modeltw wall shear stress

. v kinematic viscosity

REFERENCES1. Tyaglo, I.G. and IJL Shepelev: Dvizhenie vozdushnogo potoha k

vytyazhnomu otverstiyu [Airflow near an Exhaust Opening]. Vodosnab. Sanit. Tekh. 5:24-25 (1970). [In Russian]

2. Drkal, F.: Stromungsverhaltnisse bei runden Saugoffhungen mit Flansch. [Theoretical solution-plow conditions for Round Suction Openings with a Flange]. HLH, Z. Heiz. Lujt., Klimatech., Haustech. 21:271-273 (1970)

3. Flynn, M.R. and M.J. Ellenbecker: The potential flow solution for airflow into a flanged circular hood. Am. Ind. Hyg. Assoc. J. 4(5:318-322 (1985).

4. Flynn, M.R. and M.J. Ellenbecker: Empirical validation of theoretical velocity fields into flanged circular hoods. Am. Ind. Hyg. Assoc. J. 46:318-322 (1985).

5. Anastas, M.Y. and R.T. Hughes: Finite difference methods for computation of flow into local exhaust hoods. Am. Ind. Hyg. Assoc. J. 50:526-534 (1989).

6. Anastas, M.Y.: Computation of the initially unknown boundaries of flow fields generated by local exhaust hoods. Am. Ind. Hyg. Assoc. J. 52:379-386(1991).

7. Flynn, M.R. and C.T. Miller: Comparison of models for flow through flanged and plain circular hoods. Ann. Occup. Hyg. 52:373-384 (1988).

8. Garrison, R.P. and Y. Wang: Finite element application for velocity characteristics of local exhaust inlets. Am. Ind. Hyg. Assoc. J. 45.-983-988 (1987).

9. Flynn, M.R. and C.T.Millen The boundary integral equation method

(BIEM) for modeling local exhaust hood flow fields. Am. Ind. Hyg. Assoc. J. 50:281-288 (1989).

10. Heinsohn, R.J. and M S. Choi: Advanced design methods in industrial ventilation. In Ventilation ‘85 (Proceedings of the 1st International Symposium on Ventilation for Contaminant Control). New York: Elsevier Science Publishing Co., 1986. pp. 391-403.

11. Braconnier, R., R. Regnier, and F. Bonthoux: Efficiency of an exhaust vent on a surface treatment tank-laboratory measurements and two-dimensional numerical simulation. Cah. Notes Doc. 144, 1841:463-473 (1991). [French]

12. Kulmala, I.: Numerical calculation of airflow fields generated by exhaust openings. Ann. Occup. Hyg. 37451-467 (1993).

13. Scholer, W.: Auslegung von Einrichtungen zur Schadstofferfassung. HLH, Z. Heiz. Liift., Klimatech., Haustech. 44:506-507 (1993).

14. Ingham, D.B.: A mathematical model for pollutant control using an Aaberg exhaust hood. In Ventilation ‘94 (Proceedings of the 4th International Symposium on Ventilation for Contaminant Control). Solna: Arbete och Halsa 1994. pp. 115-120.

15. Kulmala, I: Numerical calculation of the capture efficiency of an unhanged circular exhaust opening. In Ventilation *94 (Proceedings of the 4th International Symposium on Ventilation for Contaminant Control). Solna, Sweden: Arbete och Halsa 1994. pp. 339-344.

16. Kulmala, I.: Numerical simulation of a local ventilation unit. Ann. Occup. Hyg. 38:337-349(1994).

17. Launder, B.E. and D.B. Spalding: The numerical computation of turbulent flows. Comp. Methods Appl. Mech. Eng. 3:269-289 (1974).

18. Patankar, S.V.: Numerical Heat Transfer and Fluid Flow. Washington, D.C.: Hemisphere Publishing Corp., 1980. pp. 126-131.

19. Rodi, W.: Turbulence Models and Their Applications in Hydraulics. Delft , The Netherlands: International Association for Hydraulic Research, 1984 pp 44-45.

20. Braconnier, R.: Bibliographic review of velocity fields in the vicinity of local exhaust hood openings. Am. Ind. Hyg. Assoc. J. 49:185-198 (1988).

21. Fletcher, B.: Centerline velocity characteristics of rectangular unflanged hoods and slots under suction. Ann. Occup. Hyg. 2(7:141-146 (1977).

22. Dalla Valle, J.M.: Exhaust Hoods. 2nd ed. New York: Industrial Press, 1952. pp. 11-13.

Reprinted with permission from the publisher.In: Energy and Buildings 1996. Vol. 24, pp. 133 - 136.

Paper 4

Air flow near an unflanged rectangular exhaust openingIlpo Kulmala !, Pentti Saarenrinne

Tampere University of Technology, Energy and Process Engineering, PO Box 589, 33101 Tampere, Finland

Received 1 October 1995; accepted 27 December 1995

Abstract

Turbulent air flow fields for an unflanged rectangular opening were calculated numerically using the standard k-e turbulence model. The accuracy of the calculations was verified by experimental laser Doppler anemometer velocity measurements and by comparison with previous empirical centre-line velocity equations. The results show that the air flow into an unobstructed exhaust hood can be predicted quite accurately provided that the calculation grid and the calculation domain are properly chosen.

Keywords: Local exhaust hood; LDA measurements; Local ventilation modelling

1. Introduction

Local exhaust ventilation (LEV) is widely used to remove contaminants close to the point of generation. In industry it is the preferred method when controlling the worker’s exposure to airborne contaminants, because in local ventilation the flow rates, and thereby initial and heating costs, are smaller than in general ventilation. Moreover, with general ventilation only, it may be difficult to achieve such high contaminant control which is needed to reduce the worker’s exposure near the contaminant source to acceptable levels. Traditionally, the design of LEV hoods is based on the empirical centre-line velocity formulas [1,2] and on the capture velocity, which means the velocity in front of the hood necessary to capture the contaminants into the hood [3]. While useful, this method does not take quantitatively into account the effects of that momentum of the contaminant source, disturbing air currents and obstacles in the flow field have on the efficiency of the LEV system. This deficiency is mainly due to the inability to predict the complex contaminant transport with simple empirical formulas. Thus we need quite detailed information about the flow field near the exhaust opening when determining the control effectiveness more accurately.

The first efforts for modelling air flow into exhaust hoods were based on potential flow theory, assuming an irrotational and inviscid flow. Except for boundary layers near the sur-

1 Present address: VTT Manufacturing Technology, PO Box 1701,33101 Tampere, Finland.

0378-7788/96/$15.00 © 1996 Elsevier Science S.A. All rights reserved PII 50378-7788(96 100971-1

faces, this assumption is appropriate for flows into unobstructed hoods operating at flow rates typical of industrial applications. Tyaglo and Shepelev [4] derived a solution for the three velocity components in the flow generated by an infinitely flanged rectangular hood. A model for an infinitely flanged circular opening was derived by Drkal [5], and a model with empirical modifications by Flynn and Ellenbecker [6], For unflanged rectangular or circular hoods analytical solutions have not been found. When the potential functions of the flow field are unknown, numerical methods are needed to solve the flow field. These unflanged exhaust openings have been modelled by the finite difference method [7,8], by the finite element method [ 9 ] and by the boundary integral method [10]. In most cases there was a good agreement between experimental and theoretical air velocities.

In practice, owing to wakes downstream of the obstacles in the velocity field, buoyant plumes and jets, the flow field cannot be described satisfactorily by potential flow. To solve these complex flows numerical methods are needed with a suitable turbulence model. However, so far only a few studies have been made on the simulation of a turbulent flow near local exhaust hoods [11,12], In a recent study the air flow fields into rectangular exhaust openings with different aspect ratios were predicted, but the results were not verified experimentally [ 13]. The aim of this study was to investigate the accuracy of numerical simulations in the calculation of an air flow field generated by an unflanged rectangular exhaust opening. The calculations were done by using the standard k-e turbulence model, and the results were verified with laser Doppler anemometer measurements.

134 I. Kulmala, P. Saarenrinne / Energy and Buildings 24 (1996) 133-136

Fig. 1. Calculation domain and grid.

2. Methods

In the numerical simulations an unobstructed exhaust opening drawing air from still air was modelled. The air flow was assumed to be steady, isothermal and incompressible. The time-averaged Navier-Stokes equations were solved with the FLUENT Version 3.02 computer code based on the finite volume method using the standard k-e turbulence model to represent the Reynolds stresses. In the simulations QUICK differencing scheme was used for the discretization, and the solution algorithm was SIMPLE. Sufficient convergence was assumed to have occurred when the sum of successive fractional changes (residuals) was less than 10-3.

The calculated case was a rectangular unflanged opening with an aspect ratio of 2:1 (length to width ratio). The inside width of the opening was 0.1 m and the thickness of the exhaust duct was 10 mm. A non-uniform grid was employed, with a finer grid spacing near the exhaust opening (Fig. 1). The flow field was assumed to be symmetrical with respect to the xy and xz planes, and thus only a quarter of the flow field was calculated.

The boundary conditions included a constant velocity (£7= 8.5 m s~') at the exit boundary inside the duct, and a fixed pressure at the (fee-stream boundaries. At the symmetry planes the normal velocity component and the normal derivatives of all other variables were zero. Near the exhaust duct walls the logarithmic law of the wall relation for velocity [ 14] was used to describe the region of flow lying between the wall and the first calculation point adjacent to the wall.

At the free-stream boundaries the velocity components, pressure, and turbulence kinetic energy were unknown. They are also very difficult to determine accurately. Therefore the fixed pressure boundary condition was used, and pressure and turbulence kinetic energy were set to zero at these boundaries. The fixed pressure boundary condition allows the user to input the total pressure at the boundary, instead of defining the velocity components. FLUENT then computes the normal velocity component and the static pressure at the boundary by applying Bernoulli’s equation. However, this may lead to errors in the computational results if the boundaries are too close to the exhaust opening. The flow field was thus solved with different boundary locations to determine the appropriate location of the boundaries. It was discovered that the results became independent of the boundary locations when

the distance between the exhaust opening and the free-stream boundary was greater than 6a, where a is the width of the opening. The final computational domain was thus 12a in the x direction and 6a in the y and z directions.

The effect of the grid size on the accuracy of the simulations was studied by calculating the air flow fields with different grid densities. The results indicated that, when the mesh was finer than 35X25X21, grid independent solutions can be produced. However, for better resolution all the results are for a grid with 57 X 25 X 21 nodes. Nine grid points covered the exhaust opening in the y direction and five points in the z direction.

The air velocities were determined experimentally with a laser Doppler anemometer (LDA), which is a non-intrusive optical measurement method. In order to minimise the effects of ambient disturbances on the results, the measurements were conducted in a test room with a floor area of 4.8 mX 3.6 m and a volume of 62 m3. The exhaust hood was a rectangular duct made of particle board with dimensions similar to those used in the calculations, and it was suspended in the middle of the test room at a height of 1.2 m above the floor. During the measurements the supply air into the test room was introduced through a low-velocity outlet, so that ambient air velocities around the exhaust opening were very small. The exhaust air flow-rate through the hood was 0.17 m3 s-1, corresponding to a mean hood face velocity of 8.5 m s-1, and it was measured by using a standard ISA 1932 nozzle.

The velocities were measured by a one-dimensional fibre optical set-up and a PDA processor (manufacturer DANTEC Meas. Tech.). The set-up includes a 3W Spectra Physics 164 Ar-ion laser. The main optical parameters were: focal length of the front lens 400 mm, beam separation 38 mm, wavelength of light 514.5 nm. The measures of the measurement volume were: diameter 210 p.m, length 4.4 mm, fringes separation 5.4 p.m. The probe was mounted on a computer controlled traversing system which allowed measurements to be made over a predetermined grid without the need of access to the test room.

The flow field was artificially seeded with olive oil droplets, by using a TSI Six Jet atomiser for particle generation. The seeding generator was placed far away from the exhaust opening, just downstream of the low-velocity outlet of the supply air to ensure uniform seeding inside the whole room. The mean diameter of the olive oil particles was 0.6 pm according to the manufacturer’s information. The particles tracked the flow accurately, and were still large enough to scatter sufficient light for the proper operation of the photodetector and the signal processor.

The measurement procedure was started by carefully aligning the traversing system along the centre-line of the exhaust opening. Velocities were measured both in the xy and in the xz planes at 28 X 22 different locations in front of the exhaust hood. The measured region covered an area of 0.3 X 0.3 m2. First, the velocity in the axial direction was measured in each point. Then the probe was rotated 90° around its symmetry axis, and the velocities in the vertical direction were meas

4/2

/. Kulmala, P. Saarenrinne / Energy and Buildings 24 (1996) 133-136 135

ured. 3000 samples were collected in each point. After measuring in the xy plane the exhaust duct was turned and the xz plane was measured. The results were fed into a microcomputer. Instantaneous velocity time series and other statistical quantities were calculated by the microcomputer, which was also automatically traversing the probe through predetermined coordinate points. From the measured autocorrelations estimated time macroscales were in the order of 3 ms. To ensure statistically independent sampling procedure, a dead time of 2 ms was used between samples.

3. Results

The calculated and the smoothed representations of the measured velocities in the symmetry planes are shown in Fig. 2, and the comparison between the centre-line velocities in Fig. 3. The velocities in Fig. 2 are presented as constant velocity contours, and they were calculated in the xy plane by

Fig. 2. Predicted and experimental constant velocity contours.

u/u„

------ CALCULATEDo MEASURED

------FLETCHER

0.4

Fig. 3. Predicted and experimental centre-line velocities.

V^i/lf + V2 (1)and in the xz plane by

Vt=i/u2 + W2 (2)

where U, V and W are the mean velocity components in the x, y and z directions, respectively, and they are expressed as a percentage of the average face velocity. Except very close to the exhaust opening, the predicted velocities were slightly higher than the measured ones in the symmetry planes. However, the differences were small.

A comparison of the predicted and the measured centreline velocities as a function of dimensionless distance from the exhaust opening is displayed in Fig. 3. The predictions underestimated velocities near the exhaust opening (x/A1/2<0.1), and overestimated slightly the measured values further away from the opening. The average difference between the measurements and the calculations was 3.5%. The figure also shows the generally accepted empirical equation for the centre-line velocity in front of an unflanged rectangular hood [3]

U0 0.93 +8.58a2

wherea=(x/'/A)(b/a)>3 and y3 = 0.2(x/VA) ”1/3 (4)

U is the centre-line velocity at the distance x from the exhaust opening, U0 is the mean hood face velocity, a is the width, b is the length and A is the face area of the opening. The empirical equation agrees quite well with the predictions and the measurements, although the predictions were more accurate than the empirical formula.

4. Discussion

The air flow field into an unflanged rectangular opening was calculated numerically, and the results were verified by experimental measurements with a laser Doppler anemometer, which gives accurate velocity readings without disturbing the measured air flow. When proper boundary locations and calculation grids were used, the air flow field could be predicted with good accuracy. The results indicate that numerical simulations can be a useful tool for designing local ventilation.

Further away from the exhaust opening ((x/Al/2>0.4) the predicted and measured centre-line velocities were higher than obtained from Eq. (3). Some of the differences may be due to the fact that, in the previous experiments, the velocities were measured for thin-walled tapered hoods, while in this study a thick-walled rectangular duct was investigated. In the previous studies the exhaust hood probably drew more air from behind the opening than the thick-walled duct did. Nevertheless, for practical purposes the differences are not significant.

4/3

136 /. Kulmala, P. Saarenrinne / Energy and Buildings 24 {1996) 133-136

Velocity decreases rapidly when the distance from the exhaust openings increases. Therefore, unlike supply air jets, the exhaust has little effect on the air movements in industrial halls. However, when local exhaust is used to control airborne contaminants, the transport of contaminants depends greatly on the air flow field near the contaminant source and the exhaust opening. In order to make reliable contaminant flow predictions, the air velocities near exhaust openings must be solved quite accurately, and this requires rather dense calculation grids. This fact should be taken into consideration when predicting contaminant concentrations in large industrial halls where local ventilation is used for contaminant control.

Previous studies have shown that potential flow models can predict the air flow field into unobstructed exhaust openings quite well. This leads to the conclusion that viscous and turbulent stresses do not have any great effect on the flow, except in boundary layers near the exhaust duct. However, in industrial applications there are often obstacles in the exhaust air flow field, and the contaminants have momentums which cannot be neglected (e.g. hot contaminant sources). It is likely that, in these cases, the models based on potential flow theory do not perform satisfactorily, and, for more accurate modelling, the effects of turbulence must be taken into consideration. Further research is needed to determine the applicability and limitations of computational fluid dynamics simulations when modelling local ventilation under more complex conditions.

5. Nomenclature

A hood face areaa width of rectangular openingb length of rectangular openingk turbulence kinetic energyU, V, W mean velocity components in x, y, z directionVr magnitude of velocity at a pointU0 mean velocity at the hood facex, y, z Cartesian coordinates€ turbulence dissipation rate

Acknowledgements

This study was a part of the industrial ventilation (INVENT) technology programme, financially supported by the Finnish Technology Development Centre (TEKES). The help of Mr Jouni Uusitalo on the experimental measurements is gratefully acknowledged.

References

[1] J.M. DallaValle, Exhaust Hoods, Industrial Press, New York, 2ndedn„ 1952.

[2] B. Fletcher, Centerline velocity characteristics of rectangular unflanged hoods and slots under suction, Ann. Occup. Hyg.,20(1977) 141-146.

[3] American Conference of Governmental Industrial Hygienists, Committee on Industrial Ventilation, Industrial Ventilation — A Manual of Recommended Practice, 21st edn., American Conference Governmental Industrial Hygienists, Cincinnati, OH, 1992.

[4] I.G. Tyaglo and I.A. Shepelev, Dvizhenie vozdushnogo potoha k vytyazhnomu otverstiyu (air flow near an exhaust opening), V0d0snab7.il. Sanit. Tekk.. 5 (1970) 24-25.

[51 F. Drkal, Stromungsverhaltnisse bei runden Saugoffnungen mit Flansch, Z. Heiz. IMft. Klim. Haus., 21 (1970) 271-273.

[6] M R. Flynn and M.J. Ellenbecker, The potential flow solution for air flow into a flanged circular hood. Am. lnd. Hyg. Assoc. J., 46 (1985) 318-322.

[7] M R. Flynn and C.T. Miller, Comparison of models for flow through flanged and plain circular hoods, Ann. Occup. Hyg., 32 (1988) 373- 384.

[8] M.Y. Anastas and R.T. Hughes, Finite difference methods for computation of flow into local exhaust hoods, Am. Ind. Hyg. Assoc. J., 50(1989) 526-534.

[9] R.P. Garrison and Y. Wang, Finite element application for velocity characteristics of local exhaust inlets. Am. Ind. Hyg. Assoc. J., 48 (1987) 983-988.

[ 10] M R. Flynn and C.T. Miller, The boundary integral equation method (BIEM) for modeling local exhaust hood flow fields, Am. Ind Hyg. Assoc. J., 50 (1989) 281-288.

[ 11 ] W. Scholer, Auslegung von Einrichtungen zur Schadstofferfassung, Z Heiz. Liift. Klim. Haus., (1993) 506-507.

[12] I. Kulmala and P. Saarenrinne, Numerical calculation of an air flow field near an unflanged circular exhaust opening, Staub-Reinhalt. Lufi, 55(1995) 131-135.

[13] I. Kulmala, Numerical simulation of unflanged rectangular exhaust openings. Am. Ind. Hyg. Assoc. J., 56 (1995) 1099-1106.

[14] B E. Launder and D.B. Spalding, The numerical computation of turbulent flows, Comput. Methods Appl. Mech. Eng., 3 (1974) 269- 289.

4/4

Reprinted with permission from the publisher.In: Applied Occupational and Environmental Hygiene 1997. Vol. 12, No. 2, pp. 101 -104.

Paper 5

Air Flow Field Near a Welding Exhaust Hoodllpo K. Kulmala

Tampere University of Technology, Energy and Process Engineering, P.O. Box 589, FIN-33 101 Tampere, Finland; Current address: VTT, Manufacturing Technology, P.O. Box 1701, FIN-33101 Tampere, Finland

Local ventilation is the most important method in the control of welding fumes. The present practice for dimensioning local exhaust is to select capture velocity and then calculate the required air How, assuming that the contaminant source is located on the hood centerline. Empirical and analytical formulas for these centerline velocities have been derived for simple exhaust hood configurations. However, in more complex cases the velocities may be difficult to estimate. In this study a turbulent air flow field for a flanged welding exhaust hood was calculated numerically using the FLUENT computer code based on the finite volume method. The turbulence model used in the simulation was the standard two-equation k-e turbulence model. The accuracy of the calculations was verified by experimental measurements conducted under controlled conditions. The air velocities were measured with a laser-Doppler anemometer, which is a nonintrusive optical measurement method. The results showed that the complex shape of the welding hood has little effect on the air velocities in front of the exhaust hood. The air flow into the unobstructed exhaust hood can be predicted quite accurately provided that the calculation grid and the calculation domain are properly chosen. The results give guidelines for the proper position of the hood relative to the welding point. £ 1997 AIH. Kuimala, I.K.: Air Flow Field Near a Welding Exhaust Hood. Appl. Occur. Environ. Hyg. 12(2): 101-104; 1997.

Welding processes often generate fumes and gases which may be hazardous to the health of the welder. There

fore. local exhaust ventilation is needed to reduce the contaminant concentrations to an acceptably low level in the welder’s breathing zone. Local exhaust ventilation for welding operations has been widely studied. Konig1" investigated a welding bench for fixed work sites using air velocity and temperature measurements along with flow visualization. In a German guideline detailed advice is given for the construction and design ot local exhaust systems for welding operations.(2) Li el- kens and Ticheiaar(3J studied the effect of welding current on the capture efficiency of an unflanged rectangular exhaust hood resting on a horizontal surface. These capture efficiencies were judged by visual observations. Jansson14' measured the capture efficiency of several welding hoods under controlled conditions. In another study extensive laboratory experiments were made to determine the performance of different kinds of local exhaust systems under various conditions using simulated plume and tracer gas measurements.^ A model based on potential flow theory was presented by Tum-Suden et to predict the capture efficiency for shielded metal arc welding (SMAW) operations. In this model vector addition was used to combine the exhaust hood flow field of infinitely flanged

exhaust openings with the plume velocity field produced by- welding. They found an inverse linear relationship between the measured worker exposure and predicted capture efficiency. It is difficult to estimate the model’s performance because no capture efficiency measurements were reported. This approach is. however, somewhat questionable because highly turbulent welding plumes may not be described accurately by assuming frictionless and irrotational flow.

The results of the previous studies have shown that the efficiency of an exhaust system depends on several factors such as the exhaust hood flow field, position of the welding hood relative to the welding point, ambient air currents, heat release rate, and the welder’s location and movements. Knowledge of the flow field generated by the exhaust hood is very important in estimating the hood’s ability to remove the welding fumes. There are several experimental and theoretical studies on the air flow fields near simple exhaust openings. ~]2! These studies have shown that potential flow models describe the flow field into unobstructed openings well. The flow field can also be solved quite easily for infinitely flanged openings because it is possible to calculate accurately the velocity at a point in front of the hood. However, for unflanged openings numerical methods are needed to solve the flow field. Here a major difficulty is that it is necessary to have information on the boundary conditions, which are not known beforehand.'12' The turbulent air flow fields generated bv exhaust hoods of simple geometries can also be predicted numerically with reasonable accuracy.,;UJ4' However, few studies have been published on more complex cases.

A new kind of welding exhaust hood was developed quite recently (Figure 1). This hood (manufactured by Misotek Company, Kerava, Finland) is connected to a flexible duct mounted on an easily movable arm. In the hood there are several slots to ensure an even air distribution. Since the shape of the hood might increase its effective range, this study decided to calculate the air flow field of the welding hood numerically. The results were then verified by laser-Doppler anemometer (LDA) measurements.

Methods

Numerical CalculationsThe numerical simulations modeled the unobstructed welding hood exhausting from still air. A three-dimensional Cartesian coordinate system was used so that the centerline of the exhaust duct coincided with the x axis. The calculation domain and grid are shown in Figure 2. Under calm air conditions, symmetry could be assumed with respect to the xy and xz planes, and therefore only a quarter of the flow field was calculated. The flow field was calculated for a region extending

102 l.K. Kulmaki APFLOCCUV. ENVIRON.HYG. 12(2) FEBRUARY 1997

FRONT VIEWLAMP

PLAN VIEW

SIDE VIEW

SLOTS

FIGURE 1. The welding exhaust hood.

up to 1 m in the x direction and 0.5 m in both the y and z directions. The size of the nonuniform grid was 36 X 26 X 29. The complex shape of the exhaust hood was approximated with parallelepiped cells as shown in Figure 2. The locations and sizes of the slots were similar to those of the actual hood.

A uniform velocity was assumed in the exhaust duct (boundary II) with a turbulence intensity' of 10 percent and a fixed pressure at the tree-stream boundaries (boundary 10). The exhaust flow rate was 0.17 nrVs. At the xy symmetry plane, the normal velocity component and the normal derivatives of all other variables were zero:

dU dV dk de dP(i)

above the floor. During the measurements the supply air into the test room was introduced through a low velocity outlet so that ambient air velocities around the exhaust opening were very small. The exhaust air flow rate through the hood was0.17 nrVs, corresponding to the mean velocity of 5.41 m/s in the circular exhaust duct, and it was measured using a standard ISA 1932 nozzle.

The air velocity measurements were made using an LDA (manufactured by DANTEC Measurement Technology) with a one-dimensional probe. The flow field was artificially seeded with olive oil droplets using a TSI six-jet atomizer for particle generation. The seeding generator was placed far away from the exhaust opening, just downstream ot the low velocity outlet of the supply air. to ensure uniform seeding inside the whole test room.

The measuring procedure was started by carefully aligning the traversing system with the centerline of the exhaust hood. Velocities were measured in the xy symmetry plane at 270 different locations in front of the exhaust hood. First, the velocity in the axial direction was measured in each point. The probe was then rotated 90° around its symmetry axis and the velocities in the vertical direction were measured. Three thousand samples were collected in each point. The results were entered into a microcomputer which calculated mean velocities and root mean square values of the velocity fluctuations. No attempts were made to determine turbulence length scales or dissipation rates. The microcomputer was also automatically traversing the probe through predetermined coordinate points, which allowed measurements to be made without the need to enter the test room.

Results and DiscussionThe calculated and the smoothed representations of the measured velocities are shown in Figure 3. The velocities are presented as constant velocity contours and are calculated from axial and vertical velocities by

and similarly at the xz symmetry plane. In Equation 1. U, V, and W are the mean velocity components in the x, y, and z directions, k is the turbulent kinetic energy, e is its dissipation rate, and P is the mean pressure.

The Reynolds averaged Navier-Stokes and continuity equations describing the air flow were solved numerically assuming incompressible and steady flow. The calculations were performed with the FLUENT version 3.02 computer code based on the finite volume method using the standard k-e turbulence model. The solution algorithm was a semi-implicit method for pressure-linked equations/'3' and the QUICK differencing scheme was used/16' The effects of the duct walls were taken into consideration with the wall function method."1)

MeasurementsThe air velocities in front of the exhaust hood were determined experimentally by laboratory measurements. To minimize the effects of ambient disturbances on the results, the measurements were conducted in a test room with a floor area of 4.8 X 3.6 m and a volume of 62 m3. The exhaust hood was connected to a 200-mm diameter circular duct, and it was suspended in the middle of the test room at a height of 1.2 m FIGURE 2. Calculation domain and grid.

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appl.occup. environ.hyg.12(2) FEBRUARY 1997

Air Flow Field Near a Welding Exhaust Hood 103

PREDICTED

MEASURED

^d:' 7.5

"*^15

FIGURE 3. Measured and predicted constant velocity contours in the xy symmetry plane.

They are expressed as a percentage of the average velocity in the circular exhaust duct. Where the velocities ranged from 15 to 20 percent of mean velocity, the predicted velocities differed somewhat from the measured velocities. However, especially with greater distances from the hood, the calculations agreed fairly well with the LDA measurements. As with the simple types of exhaust openings, the velocity decreases very quickly when the distance from the hood increases. Thus it may be concluded that the shape of the hood has little effect on the velocity contours farther from the exhaust hood. On the other hand, the welding hood might be less susceptible to crossdrafts, but more research is needed to verify that matter.

Figure 4 presents the smoothed contours of the measured and calculated contours of turbulent kinetic energy per unit mass:

k = -(u2 + v2 + w2) (3)

The measurements were made in the x and y directions only, and therefore the measured turbulent kinetic energy was calculated by assuming that

w2 = -(u2 + V2) (4)

xvhere w is velocity fluctuation in the z direction. The overbats in Equations 3 and 4 denote time averaging. The measured values of k differed from the predicted values, especially close to the hood and the upper slot. Here the measured velocities were also higher than predicted (Figure 3). The discrepancies may be to some extent due to the differences in the geometry of the actual hood and the model.

The results are applicable to an unobstructed hood when external air currents are small. Obstacles and surfaces in the near vicinity of the hood as well as the room air currents may alter the flow field noticeably.

In the American Conference of Governmental Industrial Hygienists (ACG1H) industrial ventilation manual11 K) the recommended capture velocities for welding operations are 0.5 to 1.0 m/s. However, several studies have shown that smaller capture velocities may be adequate to achiex’e high capture efficiency for SMAW operations. In the American Welding Society study the performance of various local exhaust systems was investigated when the hood location relative to the arc simulator was varied horizontally and vertically.!=) It can be calculated from the results that with flanged circular openings the required capture velocity was between 0.06 and 0.17 m/s when the hood centerline was located 53° or 90° to the worker and the exhaust opening was 1.5 duct diameters above the simulated arc. When the exhaust opening was directly in front of the welder (180°), the required capture velocity was 0.09 to 0.26 m/s. Higher velocities were needed for greater separation distances between the contaminant source and the hood. It was also noticed that when the exhaust hood height was increase above the value z/d = 1.5 while keeping the horizontal distance unchanged, the capture efficiency increased. The maximum capture efficiency was obtained when the height above the arc was 2.5 duct diameters (z/d = 2.5).'°' When the welding fumes were exhausted with an unflanged rectangular hood resting on surface, the required capture velocity was about 0.17 to 0.28 m/s, depending on the welding current.0’ Jansson’41 reported capture efficiencies which were over 99 percent when an unflanged 0.15-m diameter circular duct was located 0.3 m directly above the welding point. The exhaust air flow was 0.28 m3/s, corresponding to a velocity of 0.30 m/s at the welding point. With high velocity-low volume (HVLV) systems exhausting horizontally, the velocity at the source needed to be significantly higher (0.8 to 1.6 m/s).'4’ The German guideline gives capture velocities that are mostly below 0.2 m/s tor hoods exhausting directly above the welding point.’2' There are differences in the velocities required at the source for complete capture which are probably due to ditfer-

PREDICTED

MEASURED

4 0.005

FIGURE 4. Measured and predicted turbulent kinetic energy (in meters'/second2) in the xy symmetry plane.

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104 I.K. Kulmala APPL.OC.CUP. ENVIRON.HYG.12(2) FEBRUARY 1997

ences in the local exhaust systems, measuring methods, and process variables, and variations in the testing conditions. However, except for the HVLV systems, the reported capture velocities required to achieve high control of the welding fumes are dearly lower than those recommended by ACG1H. On the other hand, the experiments have usually been made under controlled and undisturbed laboratory conditions. It is likely that the ACG1H values allow for higher disturbances.

The results of this study can be used to determine the welding hood location and the exhaust flow rate required for efficient fume control, assuming the positions of the relative velocity contours do not depend on the flow rate. For example. with an air flow ot 0.31 nr'/s the mean velocity in the exhaust duct is 10 m/s. and the recommended capture velocities would correspond to the 5 and 10 percent constant velocity contours in Figure 3. On the basis of the previous studies it may be concluded that the 0.5-m/s capture velocity would be sufficient unless the cross-draft velocities are high. Thus the separation between the arc and the hood measured from the flange should be less than about 1.3D, where D is the diameter of the exhaust duct (D = 200 mm). It is advantageous to locate the hood above the weld, because the fumes rise due to thermal buoyancy and the contaminants' natural path is directed toward the hood. The maximum distance between the welding point and the exhaust hood with other flow rates can be estimated similarly.

A movable hood has the advantage over a fixed hood in that it can be moved from place to place and positioned at will. In general, the exhaust hood should be located as close to the source of the fume as possible, but because of the positional flexibility, the exhaust flow rates with a movable hood can be lower than those with a fixed hood.MV’ The control, and thus the responsibility for the correct positioning of the movable hood, rests with the welder. Therefore, the exhaust hood system must be easily movable to allow adjustment with a minimum of effort, so that the welder does not refuse to use it because of inconvenience.

ConclusionsThe air flow field near the unobstructed welding exhaust hood could be calculated fairly well provided that the calculation grid, calculation domain, and boundary conditions were properly chosen. The complex shape or the exhaust hood had little effect on the air velocities in front of the hood. Numerical modeling an advanced and flexible tool for designing and developing local ventilation. However, further research is needed to include the buoyant contaminant source in the model and to evaluate the model's accuracy.

AcknowledgmentsThis study was a part of the industrial ventilation technology program, financially supported by the Finnish Technology

Development Centre. The help of Mr. Jouni Uusitalo with the experimental measurements is gratefully acknowledged.

References1. Konig, R.: Schadstoffentsorgung an Schweissarbeitsplaczen.

Heinz-Piest-lnstitut fur Handwerkstechnik an der Technischen Universitat Hannover (1978).

2. VD1 2084 Raunilufttechnische Anlagen fiir Schweisswerkstiitten. Verein Deutscher Ingenieure, Diisseldorf (1993).

3. Liefkens. A.; Tichelaar, G. W.: Exhausting of Welding Fumes. Philips’ Welding Reporter 1(3): 19-22 (1969).

4. jansson. A.: Bestamning av infangningsformaga (Capture Efficiency of Local Exhausts). Arbete och Hiilsa 18 (1978).

5. American Welding Society: Fumes and Gases in the Welding Environment. F.Y. Speight and H.C. Cambell, Eds. American Welding Society. Miami, FL (1979).

6. Tum-Suden, K.D.: Flynn. M.R.; Goodman. R.: Computer Simulation in the Design of Local Exhaust Hoods for Shielded Metal Arc Welding. Am. ind. Hyg. Assoc. J. 51 (3): 115-126 (1990).

7. DallaValle. J.M.: Exhaust Hoods. 2nd ed. Industrial Press, New York (1952).

8. Tyaglo. LG.: Shepelev. LA.: Dvizheme vozdushnogo potoha k vytyazhnomu otverstiyu (Air Flow Near an Exhaust Opening). Vodosnab. sanit. Tekh. 5:24-25 (1970).

9. Drkal, F.: Stromungsverhaltnisse bei runden Saugoffnungen mil Flansch. Z. Heiz. Liift. Klim. Haus. 21 <8):271~273 (197(1).

10. Flynn, M.R.; Miller, C.T.: Comparison of Models for Flow Through Flanged and Plain Circular Hoods. Ann. Occup. Hyg. 32(3):373-384 (1988).

11. Anastas. M.Y.; Hughes, R.T.: Finite Difference Methods for Computation of Flow into Local Exhaust Hoods. Am. Ind. Hyg. Assoc. J. 50(10):526-534 (1989).

12. Anastas, M.Y.: Computation of the Initially Unknown Boundaries of Flow Fields Generated by Local Exhaust Hoods. Am. Ind. Hyg. Assoc. J. 52(9):379-386 (1991).

13. Scholer, W.: Auslegung von Einrichtungen zur Schadstofferfas- sung. Z. Heiz. Ltift. Klim. Haus. 44(8):506—507 (1993).

14. Kulmala. I.: Numerical Calculation of Air Flow Fields Generated by Exhaust Openings. Ann. Occup. Hyg. 37(5):451 — 467 (1993).

15. Patankar, S.V.: Numerical Heat Transfer and Fluid Flow. Hemisphere, Washington. DC (1980).

16. Leonard, B : A Stable and Accurate Convective Modelling Procedure Based on Quadratic Upstream Interpolation. Comput. Meth. Appl. Mech. Eng. !9(1):59-98 (3979).

17. Wilcox, D.C.: Turbulence Modeling for CFD. DCW Industries. Inc., La Canada, CA (1993).

18. American Conference of Governmental Industrial Hygienists: Industrial Ventilation-A Manual of Recommended Practice, 21st ed. ACGIH, Cincinnati, OH (1992).

19. Jenkins, N.; MoretonJ.; Oakley. P.; Stevens, S.: Welding Fume- Sources, Characteristics, Control. The Welding Institute. Abing- ton, Cambridge (1981).

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Paper 6

0003-4878(94)00104-9

NUMERICAL SIMULATION OF THE CAPTURE EFFICIENCY OF AN UNFLANGED RECTANGULAR EXHAUST OPENING

IN A COAXIAL AIR FLOW

Ilpo Kulmala*Tampere University of Technology, Thermal Engineering, P.O. Box 589, FIN-33101 Tampere, Finland

(Received 22 June 1994)

Abstract—Numerical simulations were used to determine the capture efficiency of an unflanged rectangular exhaust opening in a uniform flow parallel to the hood centre-line. The simulations were performed by the FLUENT computer code based on the finite volume method, using the standard k-s turbulence model. After calculating the turbulent air flow field, a large number of submicrometre particles were released in different locations in front of the exhaust opening and the destination of the particles was determined. The capture efficiency was calculated as the ratio of the number of the particles captured by the exhaust hood to the number of the particles released. The calculations were verified by tracer gas measurements. The calculated capture efficiencies were in satisfactory agreement with the experimental values. The results show also that a uniformly directed airflow may be used to enhance the capture efficiency of exhaust hoods.

NOMENCLATUREarea of exhaust opening width of rectangular opening length of rectangular opening particle diameter acceleration of gravity slip correction factorempirical constant in k-s turbulence modeltracer gas concentrationturbulence kinetic energymean pressuretimemean velocity components in x,y,z directionsfluctuating velocity components in x,y,z directionsparticle velocities in x,y,z directionsCartesian co-ordinatesturbulence dissipation ratecapture efficiencydynamic viscosityparticle densityrelaxation timerandom variables

AabdgC

ckPu,v,wu',v',w'

E

1PPT

INTRODUCTION

Local exhaust ventilation is widely used in industry to control airborne contaminants. The ability of a local exhaust hood to remove contaminants at the point of generation is

*Present address: Technical Research Centre of Finland, Manufacturing Technology, Safety Engineering, P.O. Box 1701, FIN-33101 Tampere, Finland.

22 I. Kulmala

described by the capture efficiency, which is defined as the ratio of contaminant capture rate to the contaminant generation rate (Ellenbecker et al., 1983). The capture efficiency may be measured by the tracer gas technique (Hampl, 1984; Niemela et al., 1991) but in order to predict it detailed knowledge about the flow field near exhaust openings is required.

In recent years analytical solutions based on potential flow theory have been developed for predicting the capture efficiency. Models have been developed for infinitely flanged round, rectangular and slot hoods (Flynn and Ellenbecker, 1986; Conroy and Ellenbecker, 1989; Alenius and Jansson, 1989). Flynn and Ellenbecker (1986) accounted for the dispersion of gaseous contaminants due to turbulence with an empirically determined spread parameter. Alenius and Jansson (1989) also included particle trajectory calculations for different sizes of particles in their model, but they did not take into consideration the turbulent particle dispersion.

Recently the direct capture efficiency of an exhaust hood was calculated numerically using gaseous contaminants, and the predictions were verified by air velocity and local mean age of air measurements (Madsen et al., 1993). However, the capture efficiency for a given exhaust flow rate and cross-draught velocity depends on the location of the contaminant source relative to the exhaust opening, and therefore for an accurate determination of the contaminant transport several flow fields must be calculated; this may require a lot of computational time. Another possibility would be to calculate the turbulent velocity field first and then use submicrometre particles to simulate turbulent dispersion of contaminants. By releasing a large number of particles at different locations and determining their destination the capture efficiency can be calculated conveniently. Gong et al. (1993) used this idea for predicting the performance of an aerosol sampling probe in turbulent flow. In particle tracking the computational effort depends on the numbers of particles released, but results with reasonable accuracy can be obtained in a relatively short computational time.

A previous study has shown the applicability of the k-s turbulence model in the simulation of local exhaust openings (Kulmala, 1993). In this study the capture efficiency of an unflanged rectangular opening in a uniform flow with its axis parallel to the direction of free stream was predicted. After calculating the mean velocity field the capture efficiency was evaluated by tracking large numbers of particles. The impact of the turbulence velocity fluctuations on the particle paths were simulated as Gaussian random processes. The results were validated by tracer gas measurements.

NUMERICAL MODELLING OF THE CAPTURE EFFICIENCY

The geometry of the simulated case is shown in Fig. 1. An unflanged rectangular opening with an aspect ratio b:a=2:1 was in a uniform air-flow field with its centre-line parallel to the direction of the free stream. The air flow was assumed to be isothermal and the air to be incompressible. Because of the nature of the flow case, vertical symmetry planes were assumed in the xy- and xz-planes. The calculation domain was 11a in the x direction and 5a in the y and z directions, where a is the width of the opening (a = 0.1 m). The size of the non-uniform calculation grid was 29 x 21 x 23. A uniform velocity was assumed in the exhaust duct (boundary 13) and on the inlet surface (boundary 10). A fixed pressure was assumed at boundaries II and 12.

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Numerical simulation of capture efficiency 23

11\„

b=0.2m - a = 0.1m

Fig. 1. The calculation domain and grid.

The turbulent intensity was set at 7% at the inlet boundary and at 10% in the exhaust duct.

The governing equations of turbulent flow were solved numerically using the finite- volume-based FLUENT Version 3.02 code employing the standard k-e turbulence model. The power law differencing scheme was used and the solution algorithm was SIMPLE (Patankar, 1980). Logarithmic wall functions were used to describe the nearwall regions (Launder and Spalding, 1974). As a result of the calculations the values of the mean velocity components, the turbulence kinetic energy and its dissipation rate were obtained in the calculation cells. Sufficient convergence was assumed to be reached when the sum of successive fractional changes was less than 10" 3. A solution for the three-dimensional velocity field required about 340 iterations and 119 min of cpu time on a Sun Spark Server 690 MP.

After solving the flow field the capture efficiency was evaluated by particle tracking. Non-reacting particles were released from a point source at different locations in the xy-plane in front of the exhaust duct and the destination of the particles was determined. The capture efficiency was calculated as the ratio of the number of particles captured by the exhaust hood to the number of those released. The estimates of capture efficiency were based upon 1000 particle paths at each release point. The calculations were also repeated in one case with 10000 released particles but no significant differences between the results were found. The tracking of 1000 particles took about 6 min of cpu time.

In tracking the particle paths the Lagrangian trajectory model was used where the particles are treated as discrete entities within the fluid phase. Individual trajectories were predicted as a result of the forces acting on particles. The simulation employed monodisperse particles with particle diameter of 0.1 /an. Because the particle Reynolds number was clearly less than 1 the particle motion was in the Stokes flow regime (Hinds, 1982). Thus assuming the gravity force to be in the negative z-direction and

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24 I. Kulmala

neglecting the electrostatic and other additional forces, the governing equations for the motion of a single particle are given by

du.dt

dt

* = («- Up T

= (v-yj-

(1)

(2)

dw 1—E=(w-w )—gdt t

and

(3)

(4)

where (u, v, w) and (up, vp, wp) are the air and particle velocities in the (x,y,z) directions, respectively, and g is the acceleration of gravity. The relaxation time t is defined as

pd2C(5)

where p is the density of the particle, d is the particle diameter, p is the dynamic viscosity of air and C is the slip correction factor, having the value of 2.9 for a 0.1 pm particle (Hinds, 1982). In a turbulent flow the instantaneous air velocities in Equations (l}-(3) can be divided as a sum of the time-mean and fluctuating components:

u=U+u' v=V+v’ w=W+w' (6)

When solving particle trajectories in turbulent flow the values of the instantaneous velocity components must be evaluated. While the mean values of the velocity components are obtained by solving the equations governing fluid flow, the turbulent fluctuations remain unknown. In a stochastic particle tracking method the effect of turbulence can be included in the simulations by assuming the turbulence being made up of a collection of randomly directed velocity fluctuations. In the k-e turbulence model locally isotropic turbulence is assumed so that the velocity fluctuations and the statistical properties of turbulence are independent of direction. The turbulent kinetic energy k is thus

k=ffi+tf2 + W2)=$72. (7)

The values of u,', v' and w’ which prevail during each time step are calculated byu’ = cx(|k)1/2 v' = ay(^k)112 w' = o-2(|k)1/2, (8)

where a x, ay and az are normally distributed random variables with zero mean and unit standard deviation. The kinetic energy of turbulence in each calculation cell is known from the air flow field calculations.

The velocity components are obtained by integrating the equations of particle motion over an appropriate time increment, which is restricted in two ways (FLUENT, 1989). First, the particle should not pass through more than one control volume in one time step. Second, the values of u', v' and w' are updated whenever the characteristic eddy lifetime has elapsed. Therefore, the time increment must satisfy the inequality

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At < min fL

Az;j.* vij,k wij,k

(9)

where Ax; J k, &yUjik and Azi J t are the dimensions of the calculation cell (ij,k) and uux viJk and wijk are the respective velocities. The eddy lifetime is defined as

(10)

where C„ is a constant (6'^=0.09) and e is the turbulence dissipation rate. In these calculations, the time constraint varied with location and was of order 0.001-0.10 s.

During the integration time interval At the mean and fluctuating velocities are constants so that Equations (l)-(3) can be integrated analytically, which leads to

up= C/+u,-(£/+u'-Mp0)exp(-At/T) (11)

vp=V+v'-(V+v'~ pp0)exp( - At/r) (12)

wp=W+w'-gx-(W+w' -gx - wp0)exp( - At/r), (13)

where up0, vp0 and wp0 are the initial particle velocity components. For a spherical particle with a diameter of 0.1 /im and with a density of 1000 kg m ~ 3 the relaxation time r is about 8.8 x 10"8 s. Compared to the integration time-step the relaxation time is orders of magnitude smaller and the exponential part of Equations (11)—(13) can therefore be neglected. In addition, the terminal settling velocity gx for a 0.1 /mi diameter particle is insignificant so that the equations for particle velocities becomes:

up=U+u' vp=V+v’ wp=W+w'. (14)

So it may be concluded that the small particles will adjust almost instantly to air velocity and that they follow accurately the turbulent fluctuations. The tracking of submicron particles is thus essentially equal to the tracking of fluid particles. Once the particle velocity components are obtained by solving the above equations, the particle trajectories can be calculated at any location inside the calculation domain, and the capture efficiency thereby determined.

MEASUREMENTS

The numerical calculations were verified by tracer gas measurements conducted in a test room under controlled conditions. The experimental design for measuring the capture efficiency of an unflanged rectangular duct is shown in Fig. 2. The exhaust duct with dimensions similar to those used in the simulations was positioned in front of a perforated panel outlet with a size of 0.68 x 1.2 m2. The distance between the exhaust opening and the outlet was 0.8 m. The velocity distribution of the air terminal unit was made uniform by installing a fabric felt filter downstream the perforated panel. The tracer gas used was sulphur hexafluoride (SF6) and it was discharged through a 4 mm inside diameter tube at different locations between the supply air unit and the exhaust duct. The release flow rate varied between 0.4 and 1 cm3 s_ 1 depending on the exhaust flow rate and it was kept constant by a mass flow controller (Bronkhorst type F201 C). The tracer gas concentration was measured in the exhaust duct far downstream of the

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26 I. Kulmala

Supply airLv

, AFTIR

1——i-----------------

l-A Exhaust duct

Section A-A

— 0.68 m —

0.2m 1,2m

vyyyy2yyyyyyyyyyyyyyyyy/yyy/yyy>y/yyy

Moss flow controller

Fig. 2. Measurement system.

inlet opening by a FTIR-analyser (Bomem MB 100). The exhaust flow rates used were 0.040,0.060 and 0.10 m3 s™1 corresponding to the average face velocities, Ue, of 2, 3 and 5 m s™1. The supply air flow rate was kept constant at 0.36 m3 s™1 during the measurements and thus the average face velocity, U0, at the supply outlet was 0.44 ms™1. The velocity distribution at the supply outlet was measured vertically at 20 cm intervals and horizontally at 5 cm intervals with a low velocity flow analyser (Dantec 54N50). The standard deviation of the measured velocities was 9%.

During the measurements the tracer gas release was moved at 1 cm intervals by means of a stepping motor. Each measuring point was measured four times. The capture efficiency was defined as

n=—, (15)Co

where c is the measured tracer gas concentration in the duct at a given release point and c0 is the concentration when the source was held at the hood face. The measurements were conducted on both sides of the vertical symmetry plane at the height of the opening's centre-line. The distances between the exhaust opening and the tracer gas injection point in the x direction were 0.3, 0.5 and 0.7 m.

RESULTS AND DISCUSSION

Figures 3-5 show the numerically calculated mean flow streamlines in the symmetry planes at three different exhaust flow rates. The centre-line velocities for a

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rectangular exhaust opening with and without local supply air are presented in Fig. 6. An example of the turbulence dispersion is shown in Fig. 7. The predicted and the measured capture efficiencies at three different distances from the exhaust openings are shown in Fig. 8.

When the hood is in a uniform coaxial flow field, there is a region upstream the exhaust opening, which is bounded by streamlines just entering the hood (Figs 3-5). If

Fig. 3. Streamlines in the symmetry planes with mean exhaust velocity of 2 m s 1 and supply air velocity of 0.44ms-1. The tracer gas and particle release points are shown by circles.

there were no turbulent dispersion and if the contaminants followed the mean air flow, all contaminants released inside this region would be captured. At the inlet boundary the cross-sectional area A0 of the effective capture region perpendicular to the free-stream velocity U0 can be estimated by

U0A0 = UeA, (16)

where Uc is the velocity at the exhaust opening and A is its face area. Therefore, when the free-stream velocity U0 is constant and the exhaust air flow rate is increased, the area A0 also increases which may be concluded from the streamlines entering the hood as shown in Figs 3-5.

All suction openings exhausting from still air tend to draw air from all directions and the centre-line velocity decreases rapidly with the distance from the hood opening. On the other hand, blowing air towards the hood prevents air from being drawn from behind the hood where the air is usually uncontaminated. Therefore the centre-line velocity decreases more slowly with the local supply air and reaches asymptotically a constant velocity, which is equal to the free-stream velocity. Figure 6 shows the centre-

6/7

28 I. Kulmala

Fig. 4. Streamlines in the symmetry planes with mean exhaust velocity of 3 m s 1 and supply air velocity of0.44 m s""1.

Fig. 5. Streamlines in the symmetry planes with mean exhaust velocity of 5 m s 1 and supply air velocity of0.44 m s_1.

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Un = 0.44 m s

Fig. 6. Predicted centre-line velocities with t/c = 3 m s 1.

line velocities with and without local supply air in front of an unflanged rectangular opening with an aspect ratio of 1:2. A significant increase in the velocity in front of the exhaust hood, especially at long distances from the opening, may be obtained by the use of local supply air. The trend is similar to that found in previous studies where a radial blowing jet was used to induce air flow towards a circular opening (Pedersen and Nielsen, 1993; Saunders and Fletcher, 1993).

Owing to the turbulent fluctuations particle dispersion occurs about the mean flow streamlines. This is illustrated in Fig. 7 where the trajectories of 10 particles released at each of three different points are plotted. These trajectories are based on the flow field

Fig. 7. Effect of turbulence on particle trajectories with t/e = 3 m s 1 and (/o = 0.44 ms

6/9

30 I. Kulmala

shown in Fig. 4 with a mean hood face velocity of 3 m s~1 and free-stream velocity of 0.44 ms-1. The particles were released in the xy-plane at points where the predicted capture efficiency was 100, 50 and 0%. The effect of turbulence on the particle paths is clearly seen. The particle dispersion increases with the turbulence intensity thus reducing the efficiency of the exhaust hood. Therefore low turbulence intensity in the supply air flow is essential for efficient contaminant control. In this study the turbulence intensity at the inlet boundary could not be determined accurately and therefore the choice of 7% turbulent intensity used in the calculations was somewhat arbitrary.

The measured and calculated capture efficiencies in the xy-plane in front of the exhaust opening are shown in Fig. 8. Without turbulence the capture efficiency would be a step function with values of 1 and 0. The spreading of the particle tracks due to the turbulence causes spreading of the predicted capture efficiency curve. This is in accordance with the measured efficiencies (Fig. 8). The standard deviations of the measurements are indicated by vertical lines. It can be seen that there is some asymmetry in the measured efficiencies, possibly because of spatial variations in the local supply air velocities. Nevertheless, the measured values are mostly in fair agreement with the predictions even at long distances from the exhaust opening and the width of the effective capture region is quite well predicted. This is consistent with a recent study where the capture efficiency was determined for an unflanged circular opening (Kulmala, 1994).

Turbulent flows are very complex and the assumption of isotropic turbulence with normally distributed velocity fluctuations used in this study is an idealization. In cases where there is strong anisotropy in turbulence it is anticipated that models based on the transport equations for each individual Reynolds stress component would perform better in predicting the flow field. Such flows are, for example, strongly buoyant flows. More elaborate models for particle tracking would also take into account the appropriate energy spectrum of turbulence. However, the validation of such models would need more accurate measurement systems than used in this study.

It is interesting to notice that the shapes of the capture efficiency curves in Fig. 8 are similar to those found by Flynn and Ellenbecker (1986) and by Conroy and Ellenbecker (1989). Their model used potential flow theory to describe the flow fields near flanged circular and slot hoods. The spread of contaminants was predicted assuming a leptokurtic distribution of contaminants about streamlines. In this study the same kind of results were obtained by the stochastic particle tracking method.

The results suggest that the particle tracking method may be used to describe the transport of gaseous contaminants released at a small velocity and thereby to predict the performance of local ventilation systems. In these simulations, the capture efficiencies were predicted assuming a point source of contaminant, which did not affect the previously calculated flow field near the exhaust opening. In reality, contaminants may have momentum, which must be taken into consideration in the flow field calculations.

The particle tracking method can also be used for particulate contaminants if the size distribution, density, and release velocity and direction of the particles are known. In some cases also knowledge of electrostatic and other additional forces acting on the particles may be needed. The method may also be extended to predict capture efficiencies for exhaust openings of different shapes and orientations relative to the free-

6/10


x=7a

c 0.8

^ 0.6

® 0.4

£ 0.2

♦ fi i

c 0.8

= 0.6

® 0.4

S’ 0.2

2 y/,-0.5

x=3a

c 0.8

E 0.6

® 0.4

S’ 0.2

i—|—i—r~r r"| r i i i | r~rI '"I i I

-1.5 -0.5

U I U °eFig. 8. Predicted and measured capture efficiencies at distances of (a) 70, (b) 50 and (c) 30 cm from the

exhaust opening. The calculated values are plotted as solid lines.

6/11

32 I. Kulmala

stream velocity which cannot be analysed by other means. This is necessary for the optimized design of local ventilation systems for contaminant control.

The results also show that the control of contaminants can be significantly improved by blowing air through a low-velocity inlet on the opposite side of an exhaust opening. A low turbulence intensity and a uniform velocity distribution of the supply air is essential for an optimum performance of the system. During the measurements the capture efficiency was high even at distances of about x = 5Al/2 from the exhaust opening, where A is the hood face area. On the other hand, the disturbing air velocities in the test room were low during the measurements. Higher cross-draught velocities as well as wakes caused by obstacles and workers in the flow field would be likely to reduce the performance of the system. Nevertheless, the use of local supply air with local exhaust may offer potential benefits for contaminant control.

CONCLUSIONS

The capture efficiency for an unflanged rectangular exhaust opening in a uniform air flow was calculated numerically using the stochastic particle tracking method. The results were verified by tracer gas measurements assuming that turbulence transports gaseous contaminants in the same way as it does submicron particles. The overall agreement between the predictions and the experimental results was satisfactory. The particle tracking method may be extended to predict capture efficiencies for exhaust openings of different shapes and orientations relative to the free-stream velocity.

Directing a uniform air flow with a low turbulence intensity towards an exhaust hood may be used to enhance the capture efficiency of the hood. The air can be drawn from desired regions in front of the exhaust opening and the size of the effective control area is determined by the geometry and by the ratio of supply and exhaust velocities. The use of local supply air may reduce the required exhaust air flow rates and thus reduce the overall costs of the local ventilation system. Further research is needed to evaluate the performance of this kind of system in industrial applications.

Numerical modelling may be used to gain increased understanding of the performance of local ventilation systems. It is also a useful tool for designing more efficient contaminant control systems. The accuracy of the results, however, is generally affected by the simplifications used in the calculations and especially by the reliability of the boundary conditions.

Acknowledgements—This study was a part of the industrial ventilation (INVENT) technology programme, financially supported by the Finnish Technology Development Centre (TEKES). The help of Mr Hannu Karema on the calculations and Mr Jouni Uusitalo on experimental measurements is gratefully acknowledged.

REFERENCESAlenius, S. and Jansson, A. (1989) Air flow and particle transport into local exhaust hoods. Arbete och Halsa

34.Conroy, L. M. and Ellenbecker, M. J. (1989) Capture efficiency of flanged slot hoods under the influence of a

uniform cross draft: model development and validation. Appl. ind. Hyg. 6, 135-142.Ellenbecker, M. J„ Gempel, R. F. and Burgess, W. A. (1983) Capture efficiency of local exhaust ventilation

systems. Am. ind. Hyg. Ass. J. 44, 752-755.FLUENT (1989) Version 3.02. User Manual. Creare.x Inc, Hanover, New Hampshire, U S A.

6/12


Flynn, M. R. and Ellenbecker, M. J. (1986) Capture efficiency of flanged circular local exhaust hoods. Ann. occup. Hyg. 30, 497-513.

Gong, H., Anand, N. K. and McFarland, A. R. (1993) Numerical prediction of the performance of a shrouded probe sampling in turbulent flow. Aerosol Sci. Technol. 19, 294-304.

Hampl, V. (1984) Evaluation of industrial local exhaust hood efficiency by a tracer gas technique. Am. ind. Hyg. Ass. J. 45, 485-490.

Hinds, W. C. (1982) Aerosol Technology. John Wiley & Sons, New York.Kulmala, I. (1993) Numerical calculation of air flow fields generated by exhaust openings. Ann. occup. Hyg.

37, 45M67.Kulmala, I. (1994) Numerical calculation of the capture efficiency of an unflanged circular exhaust opening.

Presented at the Ventilation '94 conference in Stockholm.Launder, B. E. and Spalding, D. B. (1974) The numerical computation of turbulent flows. Comput. Meth.

Appl. Mech. Engng 3, 269-289.Madsen, U., Breum, N. O. and Nielsen, P. V. (1993) A numerical and experimental study of local exhaust

capture efficiency. Ann. occup. Hyg. 37, 593-605.Niemela, R., Lefevre, A., Muller, J. P. and Aubertin, G. (1991) Comparison of three tracer gases for

determining ventilation effectiveness and capture efficiency. Ann. occup. Hyg. 35,405-417.Patankar, S. V. (1980) Numerical Heat Transfer and Fluid Flow. Hemisphere, Washington, DC.Pedersen, L. G. and Nielsen, P. V. (1993) Exhaust system reinforced by jet flow. In Ventilation '91 (Edited by

Hughes, R. T., Goodfellow, H. D. and Rajhans, G. S.), pp. 203-208. American Conference of Governmental Industrial Hygienists, Cincinnati, Ohio.

Saunders, C. J. and Fletcher, B. (1993) Jet enhanced local exhaust ventilation. Ann. occup. Hyg. 37, 15-24.

6/13

Reprinted with permission from the publisher. Paper 7In: Ventilation ’94, Proceedings of the 4th International Symposium on Ventilation for Contaminant Control. Solna: Arbete och Halsa 1994:18. Pp. 339-344.

Numerical calculation of the capture efficiency of an unflanged circular exhaust opening

Ilpo Kulmala

Tampere University of Technology, Thermal Engineering P.O. Box 589, FIN-33101 Tampere, Finland On leave from Technical Research Centre of Finland P.O. Box 1701, FIN-33101 Tampere, Finland

Summary

Numerical calculations were used to determine the capture efficiency of an unflanged circular exhaust opening in a uniform flow parallel to the hood centre-line. The simulations were performed by the FLUENT computer code based on the finite volume method, using the k-e turbulence model. After calculating the axisymmetric air flow field, a large number of submicrometer particles were released in different locations in front of the exhaust opening and the destination of the particles was determined. The capture efficiency was calculated as the ratio of the number of the particles captured by the exhaust hood to the number of the particles released. The calculations were verified by tracer gas measurements conducted in a test room under controlled conditions. The calculated capture efficiencies were in satisfactory agreement with the experimental results. The results suggest that particle tracking may be used for modelling the capture efficiency of exhaust hoods. A uniformly directed airflow may be used to enhance the capture efficiency of exhaust hoods.

Introduction

Local exhaust ventilation is widely used to control airborne contaminants. Since the transportation of contaminants is mainly affected by the air movements, an accurate prediction of a velocity field is essential for designing efficient local ventilation. However, the equations governing turbulent fluid flow are complex and therefore the present design practice is mainly based on empirical equations (1).

In recent years potential flow models have been developed for predicting air flow into exhaust openings (2,3,4). These models have been extended to take into consideration the effect of cross-draughts on the hood airflow field and capture efficiency (5,6). These models have been validated using wind- tunnel tests.

The potential flow assumes frictionless and irrotational flow. However, most of the air flows in practice are turbulent and in order to simulate these flows the flow field must be solved numerically modelling the effect of turbulence by a suitable turbulence model. This has become possible due to the developments in computer technology and numerical methods. Although num

erical simulations have been widely used for predicting turbulent air flows during the past two decades, only few studies have been done on the viability of numerical simulations on modelling local exhaust ventilation (7,8,9). In this study the capture efficiency of an unflanged circular opening with its axis parallel to the direction of free stream was calculated numerically using the standard k-c turbulent model. After calculating the mean velocity field the capture efficiency was evaluated by tracking large numbers of particles. The results were validated by tracer gas measurements.

Numerical methods

The air flow was assumed to be isothermal and incompressible. Because of the nature of the flow case, a cylindrical co-ordinate system was used with the axis of the exhaust duct coinciding with the z-axis. Assuming axial symmetry, the time-averaged equations governing turbulent air flow are the continuity equation

dU + 1 drV (1)dz t dr

and the momentum equations are in the axial direction

i/fE + . -1^ +1,,"/ +12^ + ay,3z dr p dz dz dz r dr dr dz

(2)

1 druV

r drdz

and in the radial direction

dz dr p dr dz dr dz(3)

1 dfPdz r dr r

where U, V, u’ and v* are the mean and fluctuating velocity components in the z and r directions, p is the mean pressure, r is the kinematic viscosity and p is the density. In Equation 3 w’ is the fluctuating velocity component in the 6 direction. In the k-e turbulence model used in this study the Reynolds stresses are expressed with the mean strain rates:

7/2

V(4)

where the turbulent kinetic energy k characterizes the intensity of turbulent fluctuations and v, is the turbulent viscosity. The above equations with additional transport equations for the turbulent kinetic energy and its dissipation rate e were solved numerically with the FLUENT version 3.02 computer code based on the finite-volume method.

n

12

Exhaustduct

13

Centre-linez

Fig. 1. The calculation domain and grid.

The calculation domain and grid are shown in Figure I. The size of the non-uniform grid was 40 x 38. A uniform velocity was assumed in the exhaust duct (boundary 13) and at the inlet surface (boundary 10). A fixed pressure was assumed at boundaries II and 12 and an axisymmetric boundary condition at the centre-line of the exhaust duct. The turbulent intensity was set at 7 % at the inlet boundary.

After solving the flow field the capture efficiency was evaluated by particle tracking. Gong et al. (10) used the same idea for predicting the performance of sampling probe in turbulent flow. Non-reacting particles with diameter of 0.1 pm were released at different radial locations in front of the exhaust duct and the destination of the particles was determined. The capture efficiency was calculated as the ratio of the number of particles captured by the exhaust hood to the number of those released. The axial distance between the release point and the exhaust opening was in each case 20 cm (about 2 duct diameters). In the particle tracking calculations the turbulent velocity fluctuations were allowed to influence the particle trajectory using a stochastic tracking technique. Because the relaxation time for a 0.1 pm particle is about 8.8x10'* s (11) the particle can be assumed to adjust instantly to velocity fluctuations. Therefore tracking of small particles could be used to visualize the effect of

7/3

Fig. 2. Example of mean streamlines (upper half) and particle trajectories (lower half) with Uc=5 m/s and U,=0.44 m/s.

turbulence and the spread of gaseous contaminants. Figure 2 shows the streamlines of a mean flow and the influence of turbulent dispersion on particle trajectories.

Measurements

The numerical calculations were verified by tracer gas measurements conducted in a test room under controlled conditions. The experimental design for measuring the capture efficiency of an unflanged circular duct is shown in Figure 3. The exhaust duct was positioned in front of a perforated panel outlet. The velocity distribution of the air terminal unit was made uniform by installing a fabric felt filter downstream the perforated panel. Sulphur hexafluoride was discharged through a 4 mm inside diameter tube at different locations between the supply air unit and the exhaust duct. The release flow rate was kept constant by a mass flow controller (Bronkhorst type F201 C). The tracer gas concentration was measured in the exhaust duct by a FTIR-analyzer (Bo-

Supply elf

/

\S-QS

Fig. 3. Capture efficiency measurement system.

7/4

mem MB 100). The exhaust flow rates used were 0.084, 0.067 and 0.042 mJ/s corresponding the average face velocities U„ 10, 8 and 5 m/s. The average face velocities U, at the supply outlet were 0.28 and 0.44 m/s. The velocity distribution at the supply outlet was measured vertically at 20 cm intervals and horizontally at 5 cm intervals with a low velocity flow analyzer (Dantec 54N- 50). The standard deviation of the measured velocities were 7 % for the lower supply velocity (0.28 m/s) and 9 % for the higher velocity (0.44 m/s).

During the measurements the tracer gas release was moved with the help of a stepping motor at 1 cm intervals. Each measuring point was measured four times. The capture efficiency was defined as

V = £ (5)'■'0

where C is the measured tracer gas concentration in the duct at a given release point and C0 is the concentration when the source was held at the hood face. The measurements were conducted on both sides of the exhaust opening at the height of the opening’s centre-line for four different ratios of Ue/U,.

Results and discussion

The predicted and the measured capture efficiencies are shown in Figure 4.The values are averages of the measurements on both sides of the opening and the standard deviation of the results is indicated by vertical lines. It may be seen that the predicted efficiencies are in fair agreement with the measured

Distanceo Ue = 5 m/s, U, =0.44 m/s • Ue = 10 m/s. V, =0.44 m/s a U„ = 5 m/s, U, =0.28 m/s ■ U,=8 m/s, U, =0.28 m/s

Fig. 4. Predicted and measured capture efficiencies.

7/5

values. The differences between predictions and experiments may be because of the spatial variations in the supply air velocities. Nevertheless, in all cases the numerical results show the same trends as the experimental results. Without the turbulence the capture efficiency would be a step function with values 1 and 0. When the turbulence dispersion is taken into account, more realistic results are obtained.

The results also show that it is possible to increase the capture efficiency of an exhaust hood by directing an airflow pattern with uniform velocity distribution towards it. This air flow transports contaminants which are released between the supply air and the exhaust into the hood. A low turbulence intensity is essential to prevent excess spreading of the contaminants. Consequently, more research is needed for studying the effect of cross-draughts and the momentum of the contaminants on the efficiency of the exhaust hood.

Numerical simulations may be used to gain increased understanding of the performance of exhaust hoods. It is also possible to simulate more and more complex flow cases on the advanced computer technology. However, experimental measurements are still needed to verify the results.

AcknowUdgemenis. This study was a part of the industrial ventilation (INVENT) technology programme, financially supported by the Finnish Technology Development Centre (TEKES). The help of Mrs Pirjo Turunen on experimental measurements is gratefully acknowledged.

References

1. ACGIH, Industrial Ventilation-A Manual of Recommended Practice (18 th edn). Lansing, Michigan 1984.

2. Tyaglo, I.G. and Shepelev, I. A. Dvizhenie vozdushnogo potoha k vytyazhnomu otverstiyu (Air Flow near an Exhaust Opening). Vodosnab. Sanit. Tekh. 5 (1970) 24-25. (In Russian)

3. Drkal, F. Stromungsverhaltnisse bei runden Saugoffnungen mit Flansch. HLH, Z. Heiz. Luft., Klimatech., Haustech. 21 (1970) 271-273.

4. Flynn, M.R. and Ellenbecker, M. J. The Potential Flow Solution for Air Flow into a Flanged Circular Hood. Am. Ind. Hyg. Assoc. J. 46 (1985) 318-322.

5. Flynn, M. R. and Ellenbecker, MJ. Capture efficiency of flanged circular local exhaust hoods. Ann. Occup. Hyg. 30 (1986) 497-513.

6. Conroy, L. M. and Ellenbecker, M.J. Capture efficiency of flanged slot hoods under the influence of a uniform cross draft: model development and validation. Appl. Ind. Hyg. 4 (1989) 135-142.

7. Braconnier, R., Regnier, R. and Bonthoux, F. Efficiency of an exhaust vent on a surface treatment tank-Laboratory measurements and two-dimensional numerical simulation. Cah. Notes Doc. 144 (1991) ND1841 463-478 [In French).

8. Heinsohn, R. J. and Choi, M. S. Advanced design methods in industrial ventilation. In Good- fellow (Ed.) Ventilation '85, Proceedings of the first international symposium on ventilation for contaminant control. Elsevier Science, New York (1986) 391-403.

9. Kulmala, I. Numerical calculation of air flow fields generated by exhaust openings. Ann. occup. Hyg. 37 (1993) 451-467.

10. Gong, H., Anand, N.K. and McFarland, A.R. Numerical prediction of the performance of a shrouded probe sampling in turbulent flow. Aerosol Science and Technology 19 (1993) 294- 304.

11. Hinds, W.C. Aerosol Technology. John Wiley & Sons, New York 1982.

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Paper 8

0003~4878(94)E0043-7

NUMERICAL SIMULATION OF A LOCAL VENTILATIONUNIT

Ilpo Kulmala*Tampere University of Technology, Thermal Engineering Laboratory, P.O. Box 589, 33101 Tampere,

Finland

(Received 21 December 1993)

Abstract—The applicability of numerical simulation in design of local ventilation was studied by calculating air flow and concentration fields for a local ventilation unit. The calculations were verified by air velocity and tracer gas measurements conducted under controlled conditions. The results of numerical modelling were in satisfactory agreement with the experiments, provided that the boundary conditions used in the calculations were reliable.

cC,,C2, C„ kp p S,*h“i

NOMENCLATUREconcentrationempirical constants in k-e turbulence model turbulence kinetic energy mean pressureshear production of turbulent kinetic energy source term for <j> air temperaturemean velocity component in direction x, velocity components in x, y, z directions magnitude of velocity at a point supply air fractionCartesian co-ordinate in tensor notationdiffusion coefficient for 4>turbulence dissipation ratedynamic viscosityeffective viscosity, /re = /i + /1,turbulent viscosity, C„pk2/£fluid densityempirical constants in k-e turbulence model dependent variable

INTRODUCTION

Local exhaust ventilation is used to capture contaminants at the point Of generation, preventing them from entering the workplace air. In addition, local supply air has been used for protection against particulate and gaseous contaminants at individual work stations (Volkwein et al., 1988; Minor, 1993; Andersson and Rosen, 1993). The combination of local supply air with local exhaust has also been used in a local ventilation unit (Andersson et al., 1993; Eloranta et al., 1993). A properly designed local ventilation system is an effective way of controlling airborne contaminants and

*On leave from Technical Research Centre of Finland, P.O. Box 656, 33101 Tampere, Finland.

338 '. Kulmala

reducing a worker’s exposure to harmful substances. Since the transport of contaminants and the efficiency of ventilation are primarily affected by the flow field generated by local exhaust openings and supply air outlets, it is very important to have detailed and accurate information on the air movements. Such information, however, cannot be provided by the present design practices of local ventilation systems based on empirical equations.

In recent years potential flow theory has been used to describe the air flow near local exhaust openings (Tyaglo and Shepelev, 1970; Drkal, 1970; Flynn and Ellenbecker, 1985). In that way the flow is idealized by assuming it to be inviscid and irrotational, which greatly simplifies its mathematical treatment. Although the potential models approximate the air flow into unobstructed exhaust openings satisfactorily, they are unable to describe common situations where turbulence or viscous forces are significant. More realistic models are obtained if the partial differential equations for continuity and momentum governing fluid flow are solved numerically along with additional differential equations which describe the effects of turbulence. This has become possible thanks to the developments in computer technology and in computational fluid dynamics (CFD) programs.

In local ventilation numerical simulations of turbulent air flow fields are relatively rare. Heinsohn and Choi (1986) calculated two-dimensional turbulent velocity and contaminant concentration fields for a push-pull ventilation system. Braconnier et al. (1991) studied numerically the effects of cross-draught on the capture efficiency for an exhaust system of a surface treatment tank. Recently, Scholer (1993) and Kulmala (1993) calculated numerically air flow fields near unobstructed exhaust openings. However, the possibilities of CFD in the modelling of local ventilation have not yet been fully utilized.

Owing to the steady development of more efficient computers and the improvement of the efficiency in the computational techniques more complex fluid flow problems can now be solved. Nevertheless, it is often difficult to verify the results of numerical calculations in practice, and the accuracy of the predictions is very much influenced by the boundary conditions used in the simulation. The aim of this study was to determine the applicability and limitations of numerical simulation when calculating local ventilation. Isothermal, three-dimensional turbulent air flow and concentration fields were calculated for a local ventilation unit using FLUENT version 3.02 computer code, and the predictions were compared to those experimental tracer gas and air velocity measurements conducted in a test room.

METHODS

The time-average steady-state air flows and tracer gas concentration distributions near a local ventilation unit were simulated using the common k-s turbulence model (Launder and Spalding, 1974). The solved general differential equations may be expressed in tensor notation as

(1)

where p is the air density, tq is the time-mean velocity component in the direction Xj, <f>

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Numerical simulation of a local ventilation unit 339

is the dependent variable, is the diffusion coefficient and Stp is the source term for <j> (Patankar, 1980). The dependent variable (p stands for different quantities, such as the mass fraction of the tracer gas, a velocity component, the turbulence kinetic energy or the dissipation rate of the turbulence. The diffusion coefficient and the source term depend on the variable <f> as shown in Table 1. In the case of the continuity equation (j> — l and Sq, 1"^ = 0.

A three-dimensional rectangular calculation grid was used in the simulation of the local ventilation unit. The size of the grid was 35 x 24 x 35 and it is shown in Fig. 1. Unfortunately, the computer code used did not include the option of boundary-fitted co-ordinate system and therefore parallelepiped cells were used to describe the local ventilation unit, which may lead to inaccurate prediction of wall shear stress at the inclined front wall. The grid used a non-uniform mesh which was finer near the exhaust and inlet openings. The number of grid points at the exhaust opening was five in the vertical direction and 11 in the horizontal direction; at the supply air inlet the number of grid points was 15 x 11 in the x and y directions, respectively. Constant values for the velocity components were given at the inlet (v= — 0.19 m s-1) and exhaust (m = — 2ms-1) openings and at the top horizontal plane (v= — 0.05 m s-1) with homogenous turbulence with an intensity of 10% of the mean air velocity. A constant pressure was assumed at other free-stream boundaries. Logarithmic wall functions were used to describe the near-wall or solid surface regions. A vertical symmetry plane was used at the centre-line to reduce the number of computational cells.

Calculations were performed using a quadratic upstream interpolation for convective kinematics (QUICK) scheme and semi-implicit method for pressure-linked equations (SIMPLE) solution algorithm. Sufficient convergence was assumed to be

Table 1. Diffusion coefficients and source terms used for isothermal numericalSIMULATION

Equation 4>

Continuity 1 0 0

Momentum “i /A

Kinetic energy k '♦s P-ps

Dissipation rate £ <

Concentration C pD + ^- 0

where /<, = C„p — is turbulent viscosity

/ie = + is effective viscosity

D is molecular diffusivity

D /'cu-t 8u8Tt----1 hr" :1 OX j

ak = l.O <Te= 1.3

is shear production of turbulent kinetic energy

<r, = 1.0 C, = 1.44 C2 = 1.92 C„ = 0.09

8/3

I. Kulmala

2.0 -

1.5 -

1.0 -

0.5 -

1.5 x (m)

Side view

Symmetry

///////

Front view

Fig. 1. Computational domain with calculation grid for the local ventilation unit.

reached when the sum of successive fractional changes (residuals) was less than 10~3. A solution for the three-dimensional velocity and concentration fields required about 18 h of CPU time on a Sun Spark Server 690 MP.

The measurements were made in a test room constructed for the study and with a floor area of 4.8 x 3.6 m and a volume of 62 m3. The local ventilation unit was equipped with local supply and exhaust ventilation. The supply air unit was placed over where the worker worked and its purpose was to reduce his or her exposure to airborne contaminant by providing clean air. The supply and exhaust air flow rates both for the general and for the local ventilation unit could be varied by frequency controllers. The air flow rates were measured by using standard ISA 1932 nozzles. During the measurements the general ventilation supply air was introduced through ceiling- mounted low-velocity outlets and the extraction was by a grille in the wall at ceiling level.

A tracer-gas method was used to study the performance of the local ventilation unit. In the experiments mean air velocity, turbulence intensity and the tracer-gas concentration were measured. The measurement system consisted of a data-logger controlled by a microcomputer, a stepping motor, a FTIR-analyser (Bomem 100) and an omni-directional air-velocity transducer (TSI Model 8470). The transducer was not suitable for measuring turbulence and therefore turbulence intensity was measured by a low velocity flow analyser (Dantec 54N50): the principle of the measurement system is shown in Fig. 2. All the measurements could be performed automatically at different measurement points. The tracer gas used was sulphur hexafluoride (SF6) and its flow was controlled by a mass flow controller (Bronkhorst type F201 C), which had an accuracy better than 1 %. Owing to the constant rate of release of the tracer gas and the carefully controlled testing conditions, any variations caused by the measurement system itself could be minimized.

In the measurements, tracer gas was injected into the air inlet duct at a rate of

8/4


Exhaust air (general ventilation)

Supply air (general ventilation)

Tracer gas release

Test roomFTIR-

anolyzer

exhaustair Micro

computerLocal supply air

DataloggerLocal ventilation unit-

Velocity transducer

Sample tube

Mass flow controller

Mixing fan

Stepping motor

/'/// 7'7 77 ///"///y // ///"//////// 7y 7 / / /"/ 7/r v ; ; ; r? ; j ; /

Fig. 2. Measurement system (not in scale).

1 mis-1 and a fan in the test room ensured that it was mixed with room air. The flow rate of the local supply air was 1501. s-1, corresponding vertical downward velocity of 0.19 m s-1. The local exhaust flow rate was 2001. s-1, giving velocity of 2 m s_1 at the exhaust opening. In order to ensure a uniform velocity distribution a honeycomb flow straightener was installed at the exhaust opening of the local ventilation unit. The measured velocities across the opening were within 5% of the mean velocity at the opening. The flow rate for the general supply air was 250 1. s~1 and the general exhaust air flow rate 2001. s “1, which gives a total air exchange rate of 23 times per h in the test room. The measurements were started after steady-state conditions had been reached in the test room. During the measurements there was nobody in the test room, nor any heat sources. The tracer gas concentration and air velocity were measured at two different heights (1.5 and 1.1 m above the floor): 1.5 m corresponds approximately to the breathing zone of a standing person. Measurements were taken in three vertical planes perpendicular to the local ventilation unit: 25 cm to the left of the centre-line, on the centre-line and 25 cm to the right of the centre-line. During the measurement cycle the velocity and concentration readings were taken at 5 cm intervals (see Fig. 3). The velocity and concentration data were stored in a micro-computer for data processing.

The fraction x of clean air below the supply air unit at each measurement point was calculated from the measured concentration c,

x = 1---- , (2)Ca

where ca is the ambient tracer gas concentration in the test room.

8/5

342 I. Kulmala

1-25-

+ '

"“I " +

+ * ' +

150 cm

109 cm

77TT77TT7T /////////Fig. 3. Location of the measurement points.

RESULTS

The agreement between numerical simulations and experimental values is greatly affected by the reliability of the boundary conditions used in the calculations. In the simulation, a uniform velocity profile was assumed downstream of the local supply air unit, which was equipped with a perforated plate. This assumption turned out to be unwarranted and to lead to unrealistic results, and the velocity distribution was therefore made more uniform by using a fabric felt filter downstream of the perforated plate in the supply air unit. After this modification the simulated results were in satisfactory agreement with the measurements.

The results from the numerical simulations are presented in Figs 4 and 5, and comparisons of the numerical calculations with the measured values in Figs 6 and 7. The predicted velocities in the figures were calculated by

F=x/u2 + v2 + wI, (3)where u, v and w are numerically calculated velocity components in the x, y and z directions, respectively. The numerically predicted velocity and concentration contours at the midplane of the local ventilation unit are shown in Fig. 4 which shows, as expected, steep velocity gradients in front of the exhaust opening. The calculations also show that there should be a region below the supply air unit, in the worker’s breathing zone, where the fraction of clean supply air is near unity. This is desirable in order to protect against ambient air contaminants as well as against contaminants generated at the working table. The fraction of clean air decreases just over the working table and near the exhaust opening where ambient air is mixed with supply air. In addition, the predictions show a region underneath the outer edge of the supply air unit where rapid changes of supply air fraction are to be expected. Figure 5 shows a three- dimensional contour where the supply air fraction is 0.9. According to the calculations, the region is anvil-shaped and situated below the air supply unit.

A comparison between calculated and measured velocities and fractions of local

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2.0 - 2.0 -

1.5 - 1.5 -

0.10 m/s1.0 - 1.0 -

0.3 X.0.5 - 0.5 -

1.5 m 1.5 m

Fig. 4. Predicted velocity contours (left) and contours of supply air fraction (right) in the vertical symmetryplane.

Fig. 5. The predicted region where supply air fraction is more than 0.9.

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344 I. Kulmala

supply air at the height of 1.5 m in the vertical plane of symmetry and 25 cm to the right and 25 cm to the left of the symmetry plane is shown in Fig. 6. Figure 7 shows the same profiles 1.1m above the floor. The standard deviations of the measured concentrations are indicated by vertical bars. It can be seen from the figures that when the local ventilation unit was operating normally the agreement between predicted and measured values is poor. At the height of 1.5 m the measured velocities were over 0.5 ms-1, and were outside the range of the velocity transducer used in the measurements, while the calculated values were about 0.2 ms-1 (Fig. 6). Furthermore, the measured supply air fraction was also consistently less than predicted.

In order to make the velocity distribution more uniform a fabric felt filter was installed downstream of the perforated plate of the supply air unit. At the supply air flow rate of 1501. s-1 used in the experiments the pressure drop over the filter was 100 Pa.

After installing the filter a more uniform, even though not constant, velocity profile was obtained below the supply air unit, as may be seen from the results in Fig. 6. In addition, with the filter the measured profiles of supply air fraction were in good agreement with predictions above 1.5 m the floor (0.5 m below the face of the supply air unit).

At the height of 1.1 m the measured concentrations are in reasonable agreement with predictions in the symmetry plane (Fig. 7), but in the plane 25 cm to the right of the symmetry plane the mixing of local supply air with ambient air was notably higher than predicted. It can also be seen that the flow field is not symmetric at greater distances from the supply air unit. This may be due to an asymmetric flow field in the test room. In the modelling it was assumed for convenience that at the upper boundary of the calculation domain there is a uniform down-flow with a vertical downward velocity of 0.05 ms-1. However, smoke tests revealed that the direction of the air velocity near the local ventilation unit is rather arbitrary, possibly because of the oscillating mixing fan in the test room. Nevertheless, the calculated velocities near the exhaust opening were in fairly good agreement with the measured values.

DISCUSSION

The air flow and the concentration fields of a local ventilation system may be predicted numerically with reasonable accuracy provided that the initial boundary conditions are realistic. The ability to do this is important in reducing the exposure of workers to airborne contaminants and in the design of local ventilation. Once a validated model has been developed, it can be used to provide a large amount of information about air movements and contaminant concentration fields which it would be impractical to obtain by measurements. The predictions can also be used to plan experimental measurements by focusing measurements at locations where steep concentration or velocity gradients are to be expected.

The measurements are consistent with the former findings, so that when the face of the supply air unit is a perforated plate the mixing of room air with supply air caused by the entrainment is considerably higher with a perforated plate than with a filter (Caplan, 1985; Chamberlin, 1990). Even though the protection provided against contaminants in the ambient air is much greater when a filter is used, the protection against contaminants generated at the working place is as yet unknown.

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Supp

ly air

fract

ion

Supp

ly air

fract

ion

Supp

ly air

fract

ion


Symmetry plane

0.3 0.5 0.7 0.9 1.1 1.3 1.5

0.6 -

0.4 ■

0.3 0.5 0.7 0.9 1.1 1.3 1.5x (m) X (m)

a Perforated plate • Perforated plate + filter — Calculated

25 cm right of symmetry plane

0.3 0.5 0.7 0.9 1.1 1.3 1.5

0.5 ■

0.4 ■

0.3 •

0.3 0.5 0.7 0.9 1.1 1.3 1.5

a Perforated plate « Perforated plate + filter

— Calculated

25 cm left of symmetry plane

0.8 ■

0.6 -

0.4 •

0.2 •

IS_t__L0.3 0.5 0.7 0.9 1.1 1.3 1.5

odd

0.3 0.5 0.7 0.9 1.1 1.3 1.5

□ Perforated plate • Perforated plate + filter

— Calculated

Fig. 6. Measured and calculated velocity and supply air fraction profiles 1.5 m above the floor.

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Supp

ly air

fract

ion

Supp

ly air

fract

ion

Supp

ly air

fract

ion

346 I. Kulmala

25 cm left of symmetry plane

0.8 •

0.6 -

0.3 0.5 0.7 0.9 1.1 1.3 1.5 0.3 0.5 0.7 0.9 1.1 1.3 1.5x (m) x (m)

o Perforated plate • Perforated plate + filter

— Calculated

Symmetry plane

0.3 0.5 0.7 0.9 1.1 1.3 1.5

>• ••••,

0.3 0.5 0.7 0.9 1.1 1.3 1.5x (m) x (m)

□ Perforated plate • Perforated plate + filter

— Calculated

25 cm right of symmetry plane

0.3 0.5 0.7 0.9 1.1 1.3 1.5

0.8 ■

0.3 0.5 0.7 0.9 1.1 1.3 1.5x (m) x (m)

o Perforated plate • Perforated plate + filter

— Calculated

Fig. 7. Measured and calculated velocity and supply air fraction profiles 1.1 m above the floor.

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For the perforated plate the measured centre-line and average velocity below the supply air unit were both significantly higher than for the fabric filter. High velocities can cause discomfort by producing draughts. The sensation of draught is affected by the combined effect of mean air velocity, air temperature and velocity fluctuations. FANGER et al. (1988) derived the following empirical expression for the percentage of workers who were dissatisfied (PD) as a result of draught in the head region:

PD = (34-fa)(F—0.05)°-62(3.14 + 0.37- F-Tu), (4)

where ra is the local air temperature (°C), Fis the local mean air velocity (ms-1) and Tu is the local turbulence intensity (%) defined as the ratio of the standard deviation of the local air velocity to the local mean air velocity. The use of a perforated plate at the supply air unit also results in high turbulence (the average turbulence intensity at the measurement points was 13% at the height of 1.5 m) while with a filter the relative turbulence intensities were somewhat lower (average 10%). Consequently, using Equation (4), the average percentage of dissatisfied workers calculated from different measurement points at the centre-line was 38% for the perforated plate. However, the draft risk equation is not strictly valid for all velocities, because velocities over 0.5 ms'1 were measured and the range of application of velocities in Equation (4) is only 0.05 m s -1 < v < 0.4 m s ~1. In addition, the model applies to seated workers when the air flow is from behind. Nevertheless, Fanger’s equation may be used for comparative purposes. When the filter was installed the predicted percentage of dissatisfied workers was only 13%. It may, therefore be concluded that the use of a filter at the supply outlet not only increases the protection factor against ambient air contaminants but also improves the thermal comfort of the local ventilation unit.

The results also show that it is possible to create regions of clean air with relatively low air velocities if the turbulence intensity of the supply air is low and the velocity distribution is uniform. The average supply air velocity in this study was only about 0.2 ms-1 whereas in previous studies it has been of the order 0.5-1.9 ms-1 (Volkwein et al., 1991; Chamberlin, 1990). It is also possible to obtain better thermal comfort with lower air velocities. On the other hand, the lower velocities may be more susceptible to the momentum of the contaminant source, cross draughts and other disturbances.

CONCLUSIONS

The numerically predicted three-dimensional velocity field for the local ventilation unit and the concentration distributions correspond satisfactorily to the experimental results. A good correlation can be achieved only by using reliable boundary values in the simulation. It was noticed in the measurements that the air flow was not uniform below the perforated plate. By installing a fabric felt filter below the perforated plate a more uniform velocity distribution may be attained, which also improves the agreement between the calculated and the experimental values. Provided that the supply air velocity distribution is uniform and the turbulence intensity of the supply air flow is low a significant reduction of ambient air contaminant concentration may be achieved without impairing thermal comfort by the use of a low-velocity supply air system installed above the work station.

The measurements and numerical simulations were restricted to conditions where

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348 I. Kulmala

the worker was absent. Further research is needed to study the effects of the worker, the momentum of the contaminant source and the cross drafts on the efficiency of local ventilation.

Numerical modelling is an advanced and flexible tool for designing and developing local ventilation. As the performance of computers increases, more detailed models may be developed. The effects of the worker, contaminant generation, hot sources, obstacles in the flow field and other considerations can be included in the model. Nevertheless, the verification of numerical calculations is still needed under controlled conditions. The tracer gas measurements proved to be a reproducible and useful method for validation.

Acknowledgements—This study was a part of the industrial ventilation (INVENT) technology programme, financially supported by the Finnish Technology Development Centre (TEKES). Halton Company is thanked for the loan of the local ventilation unit. The help of Dr Hannu Ahlstedt of Tampere University of Technology on the numerical calculations and Mr Jouni Uusitalo on experimental measurements is gratefully acknowledged.

REFERENCESAndersson, I.-M. and Rosen, G. (1993) Takmonterat lagimpulsdon ger sankt exponering for gasformiga

luftfororeningar. [Evaluation of a ceiling mounted low impulse inlet device for less air pollutants at individual workplace.] Arbete och Hdlsa 27.

Andersson, I.-M., Niemela, R., Rosen, G., Welling, I. and Saamanen, A. (1993) Evaluation of a local ventilation unit for controlling styrene exposure. In Ventilation ’91 (Edited by Hughes, R. T., Goodfellow, H. D. and Rajhans, G. S.), pp. 161-166. American Conference of Governmental Industrial Hygienists, Cincinnati, Ohio.

Braconnier, R., Regnier, R. and Bonthoux, F. (1991) Efficiency of an exhaust vent on a surface treatment tank-Laboratory measurements and two-dimensional numerical simulation. Cah. Notes Doc. 144, ND1841,463-478 (in French).

Caplan, K. J. (1985) Research and development trends and needs. In Ventilation ’85. Proceedings of the First International Symposium on Ventilation for Contaminant Control (Edited by Goodfellow, H. D.), pp. 1-17. Elsevier Science, New York.

Chamberlin, L. A. (1990) Using low-velocity air patterns to improve the operator’s environment at industrial work stations. ASHRAE Trans. 96, Part 2, 757-762.

Drkal, F. (1970) Stromungsverhaltnisse bei runden Saugoffnungen miit Flansch. Z. Heiz. Liift. Klim. Haus. 21, 271-273.

Eloranta, J., Schimberg, R. W., Hyvarinen, M., Rautio, S. and Welling, I. (1993) Use of local ventilation in welding and soldering processes. In Ventilation ’91 (Edited by Hughes, R. T., Goodfellow, H. D. and Rajhans, G. S.), pp. 69-71. American Conference of Governmental Industrial Hygienists, Cincinnati, Ohio.

F ANGER, P. O., Melikov, A. K., HaNzawa, H. and Ring, J. (1988) Air turbulence and sensation of draught. Energy Build. 12, 21-39.

Flynn, M. R. and Ellenbecker, M. J. (1985) The potential flow solution for air flow into a flanged circular hood. Am. ind. Hyg. Ass. J. 46, 318-322.

Heinsohn, R. J. and Choi, M. S. (1986) Advanced design methods in industrial ventilation. In Ventilation ’85. Proceedings of the First International Symposium on Ventilation for Contaminant Control (Edited by Goodfellow, H. D ), pp. 391-403. Elsevier Science, New York.

Kulmala, I. (1993) Numerical calculation of air flow fields generated by exhaust openings. Ann.occup. Hyg. 37, 451-467.

Launder, B. E. and Spalding, D. B. (1974) The numerical computation of turbulent flows. Comput. Meth. Appl. Mech. Engng 3, 269-289.

Minor, C. L. (1993) State-of-the art ventilation engineering principles of laminar flow and recirculation in the battery industry. In Ventilation ’91 (Edited by Hughes, R. T., Goodfellow, H. D. and Rajhans, G. S.), pp. 393-396. American Conference of Governmental Industrial Hygienists, Cincinnati, Ohio.

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Patankar, S. V. (1980) Numerical Heat Transfer and Fluid Flow. Hemisphere, Washington, DC. Scholer, W. (1993) Auslegung von Einrichtungen zur Schadstofferfassung. Z. Heiz. Liift. Klim. Haus. 44,

506-507.Tyaglo, I. G. and Shepelev, I. A. (1970) Dvizhenie vozdushnogo potoha k vytyazhnomu otverstiyu. [Air

flow near an exhaust opening.] Vodosnab. sanit. Tekh. 5, 24-25.Volkwein, J. C., Engle, M. R. and Raether, T. D. (1988) Dust control with clean air from an overhead air

supply island (OASIS). Appl. ind. Hyg. 3, 236-239.

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Paper 9

PH: 80003-4878(96)00003-8

THE EFFECT OF CONTAMINANT SOURCE LOCATION ON WORKER EXPOSURE IN THE NEAR-WAKE REGION

Ilpo Kulmala,*t Arto Saamanenj: and Seppo Enbomf*Tampere University of Technology, Energy and Process Engineering, P.O. Box 589,

FIN-33101 Tampere, Finland; and fVTT Manufacturing Technology, Safety Engineering, P.O. Box 1701,FIN-33101 Tampere, Finland

(Received in final form 16 November 1995)

Abstract—The exposure of workers in the near-wake region due to a recirculating airflow was studied experimentally and numerically. A mannequin was installed in an open-ended tunnel and tracer gas was released at several locations downstream to determine the size and location of the reverse flow region. The contaminant transport into the breathing zone was found to depend strongly on the location of the release point. The airflow field was also determined numerically assuming a steady flow and using the standard k-e turbulence model. After calculating the turbulent airflow field, a large number of submicrometre particles were released in different locations downstream of the mannequin to simulate the transport of gaseous contaminants. Although this method does not provide actual exposures, it does predict the tendencies in exposure variations due to different release points quite satisfactorily. Copyright © 1996 British Occupational Hygiene Society.

NOMENCLATURECf, empirical constant in the k-e turbulence modelH tunnel heighth height of mannequinI turbulence intensityk turbulence kinetic energyP mean pressureUi mean velocity component in direction x,ut fluctuating velocity component in direction xtXi Cartesian co-ordinate in tensor notationz height8y Kronecker delta, 8tJ= 1 for i=j and 0 otherwisee turbulence dissipation ratev kinematic viscosityvt turbulent viscosity, Cffijep fluid density

INTRODUCTION

In industry there are several operations where a horizontal unidirectional airflow is used to control airborne contaminants (George et al., 1990; Andersson et al., 1993; Guffey and Barnea, 1994). This kind of ventilation is also used in some nonindustrial applications, such as indoor firing ranges. When a person is in a unidirectional airflow, however, a region with a recirculating airflow can be created

fPresent address: VTT Manufacturing Technology, Safety Engineering, P.O. Box 1701, FIN-33101 Tampere, Finland.

512 I. Kulmala et al.

downstream. Recent studies have shown that if the contaminant source and the breathing zone are within this near-wake region, high exposure may occur (Flynn and Ljungqvist, 1995).

When fluid flows past a blunt obstacle at a sufficiently high velocity, the flow separates from the body surface forming a wake region downstream of the obstacle. This wake region is frequently associated with periodic vortex shedding. There are several studies concerning the development of such wakes for some typical cases, such as two-dimensional circular and square cylinders (Cantwell and Coles, 1983; Franke and Rodi, 1991), and cubes (Robins and Castro, 1977; Larousse et al., 1991; Murakami et al., 1991).

Although the flow past simple geometries have been widely investigated, there are few numerical and experimental studies concerning the airflow around the worker. Flynn and Miller (1991) determined the flow field around the worker by solving numerically the unsteady Navier-Stokes equations using the discrete vortex method. Ingham and Yuan (1992) determined the flow past the worker into a line sink in a wall with the boundary element method. Recently, Dunnett (1994) predicted the time-dependent flow field using the k-E turbulence model and artificial small perturbations to start the shedding process around the worker. In all these studies a two-dimensional flow was assumed and the worker was modelled as an ellipse.

It has been suggested that the transport of contaminants into and out of the near- wake zone of two-dimensional bodies is controlled primarily by vortex formation and shedding (MacLennan and Vincent, 1982). This approach was also used by George et al. (1990), who developed a simple model to determine the worker’s breathing zone concentration. Recently, Flynn et al. (1995) used a particle trajectory method to predict the worker’s exposure assuming a two-dimensional flow. Experiments have shown that the flow around the worker in a uniform airflow is three-dimensional (Kim and Flynn, 1991a) however, and therefore the airflow in the wake region may not be adequately described with two-dimensional models.

Previous investigations have studied the exposure when the contaminant source was fixed or the distance varied at the height of the chest only (Ljungqvist, 1979; George et al., 1990; Kim and Flynn, 1991b). In this study the effect of the contaminant source location on exposure was examined more thoroughly when the source location was varied within the near-wake region. Extensive wind-tunnel measurements were made to study this phenomenon. In addition, numerical modelling was applied to the solving of the flow around the worker in a unidirectional airflow. The three-dimensional steady airflow field was calculated using the standard k-e turbulence model. After calculating the airflow field, the variations in the worker’s relative exposure to a contaminant source in the near-wake region were predicted by a particle tracking method, and the results were then compared with the measurements.

EXPERIMENTAL METHODS

The experiments were carried out in a tunnel 2 m high x 2 m wide x 4.2 m deep (Fig. 1). During the measurements the air was flowing freely in the tunnel from the surrounding laboratory room. The rear wall of the tunnel was fitted with a perforated plenum in order to get better air distribution across the tunnel. The

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Worker exposure in the near-wake region 513

Sample Mast containing „ Y _ .,line injection tubes

Fig. 1. Measurement system.

exhaust air was blown outside the building and the airflow rates were regulated by controlling the speed of the fan. An anthropometric mannequin, 1.52 m tall and 0.38 m wide at the shoulder, was facing downstream on the centreline of the tunnel about 0.85 m from the tunnel face. The experiments were carried out using mean freestream velocities of 0.25, 0.375 and 0.5 m s_1 (exhaust airflow rates of 1.0, 1.5 and 2.0 m3 s"1) corresponding to Reynolds numbers of 6300, 9500 and 12700, respectively. The average turbulence intensity defined as the rms value of longitudinal velocity fluctuations to the mean longitudinal velocity of the empty tunnel was 32% measured at the location of the mannequin.

The effect of the contaminant source location on the worker’s breathing zone concentration was examined by injecting tracer gas in several points downstream of the mannequin. Tracer gas was released from 420 points within the wake region. In the vertical direction the tracer gas injection was done by using 12 tubes in a mast with the lowest release point at 0.5 m and the highest point at 1.6 m height from the floor. A point source of contaminant was modelled so that the tracer gas discharged through 6 mm inside-diameter tubes directed towards the mannequin. The tracer gas jet exit velocities were about 0.25 m s_1, and in order to study the effect of the jet momentum on the results the measurements were repeated at two distances (20 and

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514 I. Kulmala et a!.

50 cm downstream of the mannequin) by using an almost momentumless source. This was done by releasing the tracer gas through porous cylindrical diffusers with a diameter of 15 mm and a length of 23 mm. Tracer gas was released from one tube at a time. The nearest release points were 0.2 m from the mannequin and the farthest points were 0.6 m downstream the body. The release points in the horizontal direction were spaced at 0.1 m intervals. In the lateral direction release points ranged from +0.3 to —0.3 m from the centreline at 0.1 m spacing. The mast containing tracer gas injection tubes was transferred both in horizontal and lateral directions using a computer-controlled X-Y table. The tracer gas, sulphur hexafluoride, was diluted to a 2.8% mixture with air. The air-SF6 mixture was released with a flow rate of 432 ml min-1 using mass flow controllers (Bronkhorst Hi-Tech B.V., The Netherlands) to regulate the flow.

The breathing zone concentration of the tracer gas was sampled with a 10 mm dia. tube attached to the middle of the mannequin’s nose and mouth (height 1.4 m). The sampling air flow rate was 20 1. min-1 and two infra red (i.r.) spectrophotometers, one for the concentration range 2-30 ppm (BINDS, Leybold & Heraeus Gmbh, Germany) and the other for the range 0.05-2 ppm (Miran 1 A, Wilks Corporation, U.S.A.), were used to detect the sulphur hexafluoride concentration. The voltage signals from the i.r. analysers were sampled at the rate of 1 Hz for 100 s using a data logger (HP3497, Hewlett-Packard, U.S.A.) and a microcomputer. The mean values were computed from signals providing an estimate of the time-averaged concentration. The system was allowed to stabilize for 100 s before the sampling was started in each sampling point. Every freestream velocity was tested twice and the averages of the concentrations were calculated.


In the simulations, the flow field was solved assuming steady and isothermal flow. The time-averaged continuity and momentum equations can thus be written in tensor notation as

dUjdxi = 0 (1)

UjdUjdxj

iap d fdUt dufp dxj dxj \ dxj dxi , dxj (Wj), (2)

where £/,• is the mean and u. the fluctuating velocity component in the direction x„ P is the mean pressure, v is the kinematic viscosity and p is the fluid density. The study employed the standard k-e turbulence model in which the Reynolds stresses are determined by using the Boussinesq approximation

—Uilij — VdUj dUj dxj dx; (3)

where by is the Kronecker delta. The local turbulence viscosity vt is related to the kinetic energy of turbulence k and the dissipation rate of kinetic energy e by the equation

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V< — CA —, (4)

where is an empirical (usually CA = 0.09). When determining a flow field, the modelled transport equations for k and e are solved with the continuity and momentum equations. In the k-E model it is assumed that the turbulent viscosity is isotropic so that the diffusion is independent of orientation relative to the flow direction. This assumption may cause inaccurate results in strongly anisotropic flows or flow regions.

The computational domain and the calculation grid are shown in Fig. 2. A vertical symmetry plane in the centreline was introduced to reduce the number of grid points. The mannequin was modelled with rectangular cells. Inhaling was modelled with an exhaust from the head at half the sampling flow rate (10 1. min-1) because of the assumption of symmetry. The calculations were performed with two non-uniform grids of 41 x 11 x 29 and 41 x 20 x 29 points to study the effect of the grid refinement on the results. The mean-flow field was solved with a finite-volume based FLUENT version 3.02 computer code. A uniform velocity was assumed at the rear end of the tunnel and a fixed pressure at the tunnel face. The turbulent kinetic energy at the entrance was estimated by

& = l(^ + 7 + ^) = 2(/Uo):, (5)

where / is the turbulence intensity (32%) and U0 the mean freestream velocity. The inlet value of the dissipation rate was calculated by

e = C3/"J^_" 0.03//’ (6)

where H is the height of the tunnel.The shear stress at the mesh points closest to the walls and solid surfaces was

obtained from logarithmic wall functions (Launder and Spalding, 1974). The

FRONT VIEW

SYMMETRYPLANE

MANNEQUIN

Y

SIDE VIEW

4.2 m

LFig. 2. Calculation domain and grid.

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coupling between the continuity and momentum equations was achieved with the SIMPLE algorithm. The discretization scheme was QUICK. A solution for the flow field with the finer grid required about 600 min CPU time on a Sun Spark Server 690 MP. Sufficient convergence was assumed to be reached, when the sum of successive fractional changes (residuals) was less than 10-3.

After solving the flow field, the transport of airborne contaminants towards the worker’s breathing zone was predicted by particle tracking, assuming that submicron particles are transported in the same way as gaseous contaminants (Kulmala, 1995). The dispersion of the particles around the mean flow streamlines due to turbulent fluctuations was obtained by assuming that the fluctuating velocity components obey the Gaussian probability distribution with the variance depending on the local kinetic energy of turbulence. When a large number of particles were released in the near-wake region, some were captured by the exhaust in the head region, which simulated inhaling. Others were entrained in the tunnel exhaust. The calculations used the same release points as the experiments. The flight time of the particles from the release point into the head sampling depended on the location of the release point and it was 5-26 s. For a spherical particle with a diameter of 0.1 fim and with a density of 1000 kg m-3 used in the calculations the relaxation time is about 8.8 x 10-8 s. Therefore, small particles will adjust almost instantly to the air velocity and they follow the turbulent fluctuations accurately. The highest particle counts at the freestream velocity of 0.375 m s”1 were observed when the release point was in the centreline at a height of 1.2 m and 0.2 m downstream of the mannequin. This was taken to be the reference particle count value. The relative breathing zone particle count at different release points was then calculated as the ratio of particles entrained in the sampling in the head compared to the reference particle count. This method does not give contaminant concentrations and therefore the worker’s actual exposure cannot be predicted. The particle tracking method is valuable in estimating the changes in the breathing zone concentrations, however, due to spatially varying release points and also in predicting the efficiency of possible control measures. The estimates of the worker’s relative exposure were based upon 1000 particle paths from each release point. The calculations were also repeated in some cases with 10000 release particles but no significant differences between the results were found. The tracking of 1000 particles took about 3 min of CPU time.

RESULTS

The concentration contours in Fig. 3 show the measured breathing zone concentrations due to different release points in the vertical sections 10 cm to the left of the mid-plane, on the mid-plane and 10 cm to the right of the mid-plane. These results were normalized by dividing the measured concentrations by the highest concentration observed when the exhaust airflow rate was 1.5 m3 s-1. This maximum concentration (10.8 ppm) occurred when the release point was on the midplane 20 cm from the mannequin at a height of 1.2 m. The contours are for a tunnel airflow rate of 1.5 m3 s~* but the same kind of results were obtained with other exhaust flow rates. It can be seen that the breathing zone concentration depends on the height and the distance of the contaminant source from the body and as on the distance from the vertical mid-section. The exposure decreases rapidly when the

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+ 10 cm CENTRE-LINE - 10 cm

0.2 i 0.1

Fig. 3. Measured relative exposure in the vertical sections due to tracer gas release with a mean freestreamvelocity of 0.375 m s_1.

distance between the worker’s body and the contaminant source increases. As the air flows over the mannequin’s head, there is a separation, and the flow is deflected downwards. This downwash means that little contamination released above this shear layer is transported into the breathing zone. The lack of symmetry in the results was also found with the other freestream velocities and it probably reflects the spatial variations in the flow field and the asymmetry of the mannequin.

The concentration profiles with the bare tracer gas injection tube and with the momentumless source (diffusor) are compared in Fig. 4. The results are averages of five repetitions. There were some differences in the concentrations but they were not statistically significant, except for two release points at lower heights (60 and 70 cm 0.5 m downstream of the mannequin). These release points had little effect on the exposure, however, therefore it can be concluded that the momentum of the tracer gas, which was released through the tubes, had a negligible effect on the results.

The measured relative breathing zone concentrations and the calculated particle counts in the vertical mid-plane are compared in Fig. 5. These results are also normalized using the same reference concentration with the airflow of 1.5 m3 s-1 as in Fig. 3. Considering the experimental scatter in the measurements and asymmetry of the flow the overall agreement in the trends between the predictions and the experiments was quite good. The height and length of the recirculating region was well predicted. Moreover, the location of the contaminant release point producing the highest concentration was correctly predicted. The length of the region, where significant contaminant transport occurs into the breathing zone (over 10% of the reference concentration), was about 0.5-0.6 m and it was not much affected by the freestream velocity.

The calculated mean velocity vectors and [/-velocity profiles with the average freestream velocity of 0.375 m s_1 are shown in Fig. 6. This flow pattern is also in good agreement with the visual observations reported by Kim and Flynn (1991a). The predicted regions causing 10 and 80% of the reference particle count value are

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518 I. Kulmala et ai.

Jets 0.2 in

Diffusers 0.5 m

Jets 0.5 nj

Diffusers 0.2 m.2» 1.0

0 0.2 0.4 0.6 0.8 1 1.2 1.4Relative concentration

Fig. 4. Measured relative breathing zone concentration profiles with momentumless source (diffusors) and with jet. The horizontal bars indicate 95% confidence interval. The freestream velocity was 0.375 m s_1.

Fig. 5. Measured relative exposures and predicted relative particle counts in the vertical mid-plane withvarious mean freestream velocities.

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-0.2 0 0.2 0.4

1-4 - l\ x _'V\ -x VW "x "x

w.. > > >1.0.-

x (m) U (ms ’) U (ms *) U (ms"')

Fig. 6. Predicted mean flow field and velocity profiles downstream of the mannequin in the vertical midsection.

Fig. 7. Predicted mean flow field and velocity profiles downstream of the mannequin in a horizontal plane. The velocities have been reflected in the plane of symmetry.

also overlaid in the figure. Figure 7 shows the mean velocity vectors projected onto a horizontal plane at a height of 1.1 m parallel to the main flow direction. From these figures the flow pattern in the reverse flow region can be clearly seen. For clarity, the length of the velocity vectors is proportional to the square root of the velocity magnitude. These mean air velocity fields also help us to understand the contaminant transport into the breathing zone and to explain the measured exposures. In the vertical section approximately above the mannequin’s hip level (z>0.8 m, Fig. 6) the air circulates clockwise and contaminants released in this region may enter the

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breathing zone. On the other hand, below the hip level the air circulates mainly horizontally and the contaminants released in this region do not significantly enter the breathing zone.

An increase in the grid density did not greatly affect the predicted velocities, although the recirculation length was higher with the coarser grid. It is difficult to say whether grid-independent solutions were obtained because further refinements in the grid density were not possible due to the limitations of the computer resources.

The predicted mean velocities in the reverse flow were clearly lower than the freestream velocities. Maximum velocities towards the mannequin depended somewhat on the freestream velocity but were below 0.1 m s~1. The predictions therefore suggest that the reverse flow momentum is so low that the worker’s exposure could possibly be controlled by appropriate measures.

DISCUSSIONThe aims of this study were to investigate the effect of the contaminant source

location on the worker’s exposure in the near-wake region and the applicability of numerically modelling this situation. The flow field downstream of the worker is very complex and the results revealed that the exposure depends greatly on the location of the contaminant source. Despite the deficiencies of the simulations these variations could be predicted quite well in the centreline assuming a steady flow. The contaminant source position which caused the greatest exposure was predicted surprisingly well, but asymmetry was found in the measured concentration fields contrary to the calculations where symmetry was assumed about the vertical midplane.

An important feature in the near-wake region is the size and location of the recirculation zone downstream of the worker because contaminants released in this region can enter the breathing zone. The mean recirculation length depended little on the freestream velocity and it appeared to be about 1.5 times the mannequin’s width downstream of the body. The breathing zone concentration decreases rapidly when the distance of the contaminant source from the body increases. It was also observed that significant contaminant transport toward the breathing zone occurs only above the hip level (zjh >0.53). These findings are in general agreement with previous studies (George et al., 1990; Kim and Flynn, 1991a).

In the numerical model, the transport of contaminants into the breathing zone depends on the mean flow field as well as on the turbulent dispersion of the contaminants about the mean flow streamlines. This, in turn, depends on the local state of turbulence which in this model was characterized by the turbulent kinetic energy and its dissipation rate. Therefore, for accurate breathing zone concentration predictions both the mean velocity field and the turbulent kinetic energy should be correctly calculated.

The accuracy of numerical calculations usually depends on several components of the simulation method, such as the applicability of the adopted turbulence model, computation grid, reliability of the boundary conditions and the discretization scheme. In these calculations the factors having the greatest effect on the accuracy were the geometrical approximations, the presumption of symmetric and steady flow, and the shortcomings of the fc-e turbulence model.

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The tracer gas measurements indicated asymmetry about the centreline although the measured maximum concentration levels were observed in the vertical midsection. The mannequin’s arms and body were also in a somewhat asymmetric position. In addition, the mannequin was approximated quite crudely by parallelepiped cells. The calculations also assumed symmetric velocity distribution about the centreline at the entrance but the air velocity measurements revealed that the velocity was non-uniform and somewhat asymmetric. The spatial variation of the velocities was 27%. This kind of variation is, however, quite common in industrial ventilation applications.

It is well known that the periodic vortex shedding frequency of flows past slender two-dimensional bodies is nearly constant for a wide range of Reynolds number. The frequency depends on the aspect ratio of the obstacle, however, so that the Strouhal number decreases with decreasing aspect ratio. In addition, it has been discovered (Sakamoto and Arie, 1983) that the level of fluctuating velocity caused by vortex shedding approaches the level of other irregular velocity fluctuations when the aspect ratio is less than 1.0 for square cylinders and less than 1.5 for circular cylinders, suggesting that the periodic vortex shedding disappears. Kim and Flynn (1991a) measured the shedding frequencies at different heights in the wake region of a mannequin and found that the prominent frequency peaks characterizing the vortex shedding frequency depended on the height. They found prominent frequency peaks between the waist and hip levels (0.44<zjh<0.54) but not above the elbow level (z/ h > 0.63). It can be concluded, therefore, that the flow past a worker in uniform flow may be periodic in some regions. Steady-state calculations do not reveal this phenomenon and are probably erroneous in predicting the mean flow field in these regions since the strong momentum exchange by periodic vortex motion is not accounted for in this approach (Franke and Rodi, 1991). Nevertheless, the results proved that the most important region affecting the worker’s exposure is between the waist and the head level and that the flow field in this region may be predicted reasonably well with steady flow calculations.

The k-s model is currently perhaps the most commonly used turbulence model for practical calculations and it has been applied successfully to a wide range of flow predictions. Recent studies have indicated that the standard k-e model may not predict the flow past bluff bodies very well (Obi et al., 1990; Franke and Rodi, 1991; Murakami et al., 1991), however, the inaccuracies are caused by the assumption of isotropic turbulent viscosity and gradient hypothesis for the Reynolds stresses. Better agreement with the measured flow fields were obtained with the Reynolds stress models, which take the turbulence anisotropy and flow history effects on the turbulence into account. Even these more sophisticated models were not fully satisfactory, however, and it was concluded that the most accurate results may be obtained using the large-eddy simulation (LES). In this approach the large eddies are computed and only the smallest eddies are modelled. The LES is considered to be a potentially promising method, but so far the very large computational resource requirements have limited its application to research topics. On the other hand, the differences between the geometry of the mannequin in reality and in the simulations, spatial variations of the flow velocities and possible periodicities of the flow may have greater effect on the results than the turbulence model.

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It has been suggested (George et al., 1990; Kim and Flynn, 1991a) that exposure can be estimated by assuming the flow to be two-dimensional and that the contaminant removal is primarily due to the vortex shedding. The results of this study show, however, that the flow is three-dimensional and that the exposure strongly depends on the distance between the contaminant source and the worker’s body, as well as on the height and distance from the centreline. The measurements also show that the upper recirculation zone in the near wake is the most important region causing worker’s exposure. Furthermore, the relatively good agreement between calculations and experiments implies that despite the imperfections of the computational method used and the complexity of the real flow the three- dimensional steady-state simulations can give useful results when predicting the flow field in this region.

Kim and Flynn (1992) studied the source momentum effect on the worker’s exposure in a wind tunnel by releasing gas through jets directed outwards from the mannequin. They discovered that a source momentum as small as the momentum of jets used in this study caused a reduction in breathing zone concentrations. Contrary to their results, the effect of the source momentum in this study was not statistically significant. The data in their study do not permit a direct comparison, however, because the jet directions were different and the exact contaminant release point was not reported. The nearest release point in this study was 0.2 m from the mannequin, while in Kim and Flynn’s study the source was probably located closer to the mannequin.

The results are applicable when a stationary worker is in a uniform airflow and the momentum of the contaminant source is negligible. These restrictions are rarely met under actual working conditions. However, the results are useful in understanding the transport of contaminants in the near-wake region. One of the advantages of numerical simulations is the possibility to study various effects on the exposure once a verified model has been developed. Research is under way to examine how to reduce the exposure effectively.

Acknowledgements—This work was financially supported by the Finnish Work Environment Fund (TSR) and Finnish Technology Development Centre (TEKES).

REFERENCESAndersson, I.-M., Niemela, R., Rosen, G. and Saamanen, A. (1993) Control of styrene exposure by

horizontal displacement ventilation. Appl. occup. Environ. Hyg. 8, 1031-1037.Cantwell, B. and Coles, D. (1983) An experimental study of entrainment and transport in the turbulent

near wake of a circular cylinder. J. Fluid Mech. 136, 321-374.Dunnett, S. J. (1994) A numerical investigation into the flow field around a worker positioned by an

exhaust opening. Arm. occup. Hyg. 38, 663-686.Flynn, M. R., Chen, M-M., Kim, T. and Muthedath, P. (1995) Computational simulation of worker

exposure using a particle trajectory method. Ann. occup. Hyg. 39, 277-289.Flynn, M. R. and Ljungqvist, B. (1995) A review of wake effects on worker exposure. Ann. occup. Hyg. 39,

211-221.Flynn, M. R. and Miller, C. T. (1991) Discrete vortex methods for the simulation of boundary layer

separation effects on worker exposure. Ann. occup. Hyg. 35, 35-50.Franke, R. and Rodi, W. (1991) Calculation of vortex shedding past a square cylinder with various

turbulence models. In Proc. Eight Symposium on Turbulent Shear Flows, Technical University of Munich, Germany, pp. 20.1.1-20.1.6.

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George, D. K., Flynn, M. R. and Goodman, R. (1990) The impact of boundary layer separation on local exhaust design and worker exposure. Appl. occup. Environ. Hyg. 5, 501-509.

Guffey, S. and Barnea, N. (1994) Effects of face velocity, flanges, and mannikin position on the effectiveness of a benchtop enclosing hood in the absence of cross-drafts. Am. ind. Hyg. Ass. J. 55, 132— 139.

Ingham, D. B. and Yuan, Y. (1992) A mathematical model for the air flow around a worker near a fume cupboard. Ann. occup. Hyg. 36, 441-453.

Kim, T. and Flynn, M. R. (1991a) Airflow pattern around a worker in a uniform freestream. Am. ind. Hyg. Ass. J. 52, 287-296.

Kim, T. and Flynn, M. R. (1991b) Modeling a worker’s exposure from a hand-held source in a uniform freestream. Am. ind. Hyg. Ass. J. 52, 458-463.

Kim, T. and Flynn, M. R. (1992) The effect of contaminant source momentum on a worker’s breathing zone concentration in a uniform freestream. Am. ind. Hyg. Ass. J. 53, 757-766.

Kulmala, I. (1995) Numerical simulation of the capture efficiency of an unflanged rectangular exhaust opening in a coaxial air flow field. Ann. occup. Hyg. 39, 21-33.

Larousse, A., Martinuzzi, R. and Tropea, C. (1991) Flow around surface-mounted, three-dimensional obstacles. In Proc. Eight Symposium on Turbulent Shear Flows, pp. 14.4.1-14.4.6.

Launder, B. E. and Spalding, D. B. (1974) The numerical computation of turbulent flows. Comput. Meth. appl. Mech. Engng 3, 269-289.

Ljungqvist, B. (1979) Some observations on the interaction between air movements and the dispersion of pollution. Document D8. Swedish Council for Building Research, Stockholm, Sweden.

MacLennan, A. S. and Vincent, J. H. (1982) Transport in the near aerodynamic wakes of flat plates. J. Fluid Mech. 120, 185-197.

Murakami, S., Mochida, A. and Hayashi, Y. (1991) Scrutinizing k-e evm and ASM by means of LES and wind tunnel for flow around cube. In Proc. Eight Symposium on Turbulent Shear Flows, pp. 17.1.1- 17.1.6.

Obi, S., Peric, M. and Scheuerer, G. (1990) Finite volume computation of the flow over a square rib using a second order turbulence closure. In Engineering Turbulence Modelling and Experiments (Edited by Rodi, W. and Ganic, E ), pp. 185-194. Elsevier, New York.

Robins, A. G. and Castro, I. P. (1977) A wind tunnel investigation of plume dispersion in the vicinity of a surface mounted cube-I. The flow field. Atmospheric Environment 11, 291-297.

Sakamoto, H. and Arie, M. (1983) Vortex shedding from a rectangular prism and a circular cylinder placed vertically in a turbulent boundary layer. J. Fluid Mech. 126, 147-165.

Werner, H. and Wengle, H. (1991) Large eddy simulation of turbulent flow over and around a cube in a plate channel. In Proc. Eight Symposium on Turbulent Shear Flows, pp. 19.4.1-19.4.6.

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Manuscript prepared for publication. Paper 10

NUMERICAL SIMULATION OF A LATERAL EXHAUST HOOD FOR A HOT CONTAMINANT SOURCE

Dpo KulmalaVTT Manufacturing technology

Safety Engineering,P.O. Box 1701, FIN-33101 Tampere, Finland

Pentti Saarenrinne Tampere University of Technology

Energy and Process Safety Engineering, P.O. Box 565, FIN-33101 Tampere, Finland

Abstract - A lateral exhaust hood for a hot contaminant source was modelled numerically. The calculations were made with the FLUENT computer code using the standard k-e turbulence model. The accuracy of the simulations was assessed by comparing the predictions with laser-Doppler anemometry and capture efficiency measurements. The calculated mean velocities were in a reasonable agreement with the experimental values. However, the turbulent velocity fluctuations were poorly predicted both in the plume region and near the exhaust opening. The simulations predicted also clearly higher capture efficiencies than those observed experimentally.

NOMENCLATURE

C tracer gas concentrationCM empirical constant in the k-e turbulence modelcp specific heatE capture efficiencyF source buoyancyG tracer gas release rateg acceleration of gravityk turbulence kinetic energyP mean pressurePrT turbulent Prandtl numberQ convective heat release rateq volumetric air flow rater radial coordinateT mean temperaturet turbulent fluctuating temperatureUj mean velocity component in the x; directionU, V, W mean velocity components in the x, y and z directionsu, v, w turbulent fluctuating velocity components in x, y and z directionsz0 location of virtual origin6,i Kronecker delta, 5^=1 for i=j and 0 otherwisee turbulence dissipation ratep dynamic viscosity of fluidpx turbulent viscosityp fluid density(J) volumetric heat generation rate

Subscriptsa ambient conditionCL centreline valueLE local exhaust

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INTRODUCTION

Local exhaust ventilation is frequently used to remove buoyant plumes containing harmful contaminants. Such plumes are generated, for example, by welding and by several processes in metallurgical industry. In these cases the fluid motion governing the dispersion of contaminants is highly turbulent and influenced by both the exhaust hood flow field and the buoyancy source. For the design of efficient contaminant control it is therefore necessary to predict the combined flow field near the exhaust hood accurately.

Several experimental studies have been made on turbulent buoyant plume in stagnant environment (Rouse et al., 1952; Ogino et al., 1980, Papanicolaou and List, 1988, Shabbir and George, 1994). Various turbulence models have also been applied to predicting buoyancy driven flows. (Madni and Fletcher, 1977; Chen and Chen, 1979; Malin and Younis, 1990). However, the interaction between a hot contaminant source and local exhaust is much less investigated. Bender (1979) studied canopy hoods and Cesta (1989) lateral exhaust hoods for buoyant sources by using scale models. Turn Suden et al. (1990) presented a model based on potential flow theory to predict the capture efficiency for welding operations. In this model vector addition was used to combine the exhaust hood flow field of infinitely flanged exhaust openings with the plume velocity field produced by welding. The model was tested by comparing a welder’s breathing zone concentrations with the predicted capture efficiencies. However, no measurements on velocity or capture efficiency were reported.

In this study a lateral hood exhausting near a hot contaminant source was investigated both experimentally and numerically. In the simulations the k-e model was used for turbulence closure. The calculations were then verified with air velocity and capture efficiency measurements. It is known that the two-equation turbulence model does not perform very well in predicting the axial turbulent transport in buoyant flows (Shabbir and Taulbee, 1990). However, since the k-e model is so widely popular, it is important to find out how reliable this method is when applied to practical buoyant flow calculations. Although it is anticipated that more advanced turbulence models, such as the Reynolds stress models, should give more accurate results, these models require considerably more computer time and can cause serious convergence problems in buoyant flow simulations (Davidson, 1990).

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EXPERIMENTAL METH ODS

The air velocity and capture efficiency measurements were made in a test room under controlled conditions to minimize the effect of ambient disturbances on the results. The test room had a floor area of 4.8 m x 3.6 m and a ceiling height of 3.6 m. The general ventilation supply air for the test room was through a ceiling mounted low-velocity diffuser, and the extraction was from a grille in the wall at the ceiling level. A 0.20 m x 0.10 m unflanged rectangular duct was installed in the middle of the test room at the height 1.0 m above the floor (Figure 1). The heat source was a soldering iron with the diameter of 40 mm and the height of 80 mm, and it was placed in front of the exhaust hood 110 mm below the exhaust duct centreline. The floor below the heat source was covered with aluminium foil in order to minimize the heating of the floor due to radiant heat transfer. The vertical temperature distribution in the test room was measured with thermistors at six different heights between 0.5 m and 2.5 m above the floor. During the experiments the vertical temperature gradient was quite small, about 0.1 K m"1.

The convective release heat transfer rate of the soldering iron was determined experimentally by temperature measurements in the exhaust duct at a known exhaust flow rate. First the temperature Ta was measured in the exhaust duct without the heat source. Then the downwards facing exhaust hood was placed 20 cm above the heat source. At this distance all the heated air was captured by the hood while the flow near the heat source was almost undisturbed. The temperature TLE was measured again in the exhaust duct and the convective heat release rate Q was calculated by

2 = ?pc.(r„j-r^ (i)

where q is the exhaust flow rate, p is the air density and cp is the specific heat of air. The measured heat transfer rate was 100 W. This is of the same order as is released by convection in shielded metal arc welding operations.

The tracer gas method was used for the capture efficiency measurements. Sulphur hexafluoride was released around the heat source at a constant rate and the concentration was measured both in general and local ventilation exhaust ducts with a FTIR analyser. The tracer gas release rate was regulated with a mass flow controller (Bronkhorst type F201 C), and the exhaust air flow rates were measured with standard ISA 1932 nozzles. The distances between the exhaust opening and the centre of the heat source in the x direction were 0.20, 0.25 and 0.30 m. At each distance the capture efficiencies were measured with several exhaust flow rates and each flow rate was repeated at least three times. In order to mix the tracer gas with the plume flow evenly, the tracer release was through a copper ring of 44 mm in dia

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with four 1 mm holes installed around the soldering iron. The measurements were started after reaching steady-state conditions in the test room. From the measured concentrations the direct capture efficiency E was calculated by

G(2)

where G is the tracer gas release rate, CLE is the tracer gas concentration in the exhaust duct and Ca in the general ventilation exhaust. Thus, when the exhaust is 100 % efficient, all the tracer is removed by the local exhaust only, and the ambient concentration in the test room is zero.

The air velocities in front of the exhaust duct were measured with a laser Doppler anemometer (EDA), which is a non intrusive optical measurement method. Velocities were measured on the hood centreline in horizontal and vertical directions. During these experiments the horizontal distance between the heat source and the exhaust duct was 20 cm. The measurements used a one-dimensional fibre optical set-up and a PDA processor (DANTEC). The set-up included a 3W Spectra Physics 164 Ar-Ion laser with a focal length of the front lens 400 mm. The flow field was seeded by olive oil droplets generated with a TSI Six Jet atomizer. The seeding generator was placed far away from the heat source to ensure uniform seeding inside the whole room. The mean diameter of the droplets was 0.6 pm according to the manufacturer's information.

In order to check out the reliability of the measurement system and the accuracy of the numerical simulations when calculating plumes, measurements were also made for the pure buoyant plume. In these measurements axial velocities were measured at six vertical levels above the heat source without the local exhaust.

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The experimentally studied cases were simulated numerically using FLUENT version 4.32 computer code, which is based on the finite volume method. The calculations were made employing the common k-e turbulence model assuming steady flow. The discretisation scheme was QUICK, and SIMPLE algorithm was used for solving the transport equations.

The time-averaged momentum and energy equations can be expressed in tensor notation

-(P(W = -^

* (3)

(4)

where U; is the mean and ut fluctuating velocity component in the direction x,, P is the mean pressure, p is the dynamic viscosity, PrT is the turbulent Prandtl number and (}) is the volumetric heat generation rate. The air density p is calculated by the ideal gas law. The correlations of fluctuating quantities pu,Uj and pu; t in equations (3) and (4) represent the transport of momentum and heat due to the turbulent motion. These turbulent fluxes are related in the k-e model to the mean gradients of dependent variables through an eddy viscosity

au. au(5)

p« ar(6)

where PrT is assumed to be a constant and the eddy viscosity pT is calculated by

F<v= Pc, e (7)

where k is the turbulent kinetic energy and e is its isotropic dissipation rate. The commonly used value of the constant CM = 0.09 is chosen on the basis of

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experiments in non-buoyant flows, in which the production and dissipation of the turbulence energy are in approximate balance (Rodi, 1984). However, universality of the constant CM can not be expected and it may acquire a somewhat different value even in fairly simple flows.

The geometry of the simulated local exhaust hood near the heat source is shown in Fig. 1. An unflanged rectangular opening with dimensions similar to those used in the experiments was exhausting laterally. The heat source was modelled with rectangular cells with a surface area equal to the soldering iron used in the measurements. Vertical symmetry was assumed in the xz-plane. The calculation domain was 1.2 m in the x direction, 0.6 m in the y-direction and 1.2 m in the z direction. Two non-uniform calculation grids were used in the simulations with grid sizes of 32 x 21 x 36 and 62 x 32 x 62 cells. A uniform velocity was assumed in the exhaust duct and a fixed pressure at freestream boundaries. A heat flux boundary condition was specified at the surface of the hot source so that the convective heat release rate was 100 W. The heat exchange due to radiation was omitted. The calculations were made for the same distances between the heat source and the exhaust opening as in the experiments.

SYMMETRY PLANE

g

EXHAUST DUCT\ HEAT SOURCE

0______________________________________ J

Figure 1. Geometry of the studied case.

After solving the air velocity field, the capture efficiency was calculated using the particle tracking method. This method allows a simulation of the gaseous contaminant dispersion due to turbulence (Kulmala, 1995). A large number of submicrometer particles was released around the heat source at the same locations as in the experiments and their destination was determined. In a turbulent flow field the particle paths are dispersed randomly by the turbulence, so that an estimation of

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the contaminant dispersion can be obtained. The capture efficiency was then calculated as the ratio of the number of particles captured by the exhaust hood to the number of those released. The estimates of capture efficiency were based upon 1000 particle paths at each release point.

Due to the computer resource limitations finer calculation grids were not possible. On the other hand the required grid densities for the exhaust hood flow field predictions are known from previous studies (Kulmala and Saarenrinne, 1996). Therefore grid dependency was studied separately for the buoyant plume. These calculations were made using both three dimensional rectangular and cylindrical coordinate systems. With cylindrical co-ordinates axial symmetry could be assumed under calm ambient conditions, and the axis of the heat source coincided with the z-axis. In this geometry the grid refinement tests were made using 62 x 32, 82 x 42, 162 x 82 and 322 x 162 non-uniform grids.

In the pure plume calculations the model constant values and Prx were adjusted to produce a good agreement of the predicted and the measured shear stress u w (Shabbir and George, 1994), which was also reflected in a reasonable prediction of the mean vertical velocities. The calculations were made with values CM in the range 0.07-0.13 and PrT 0.7-1.0. These values of the turbulent Prandtl number are in the same range as observed in comprehensive round turbulent plume measurements (Shabbir and George, 1994). On the basis of the results the values of CM =0.11 and PrT =0.85 were chosen.

RESULTS AND DISCUSSION

The measured and the predicted mean centreline velocities for the pure plume are plotted in Fig. 2 versus the dimensionless distance z/D from the heat source. Figure 3 illustrates the predicted contours of constant density with two exhaust flow rates. The mean velocities with local exhaust are shown in Figures 4 and 5 and turbulent stresses in Figures 6 and 7. Figure 8 presents the comparison of predicted and measured capture efficiencies.

Previous plume flow studies have shown that for the round plume in a uniform environment the mean vertical velocity W varies in the decay region as

w = A, p TcX!

fflz -mexp(-BA(r/zf) (8)

where g is the gravitational acceleration, Q the convective heat release rate, z is the vertical distance above the virtual origin of the plume and r is the distance from the plume axis. Although there is a consensus about the general form of the plume, there has been some disagreement about the centreline value of the mean velocity and plume spreading rate. A curve fit of the measured velocities gives A%=3.3 and Bv=57, which are in close agreement with the values of 3.4 and 58 obtained by Shabbir and George (1994) in their more extensive plume measurements. The differences are quite small, thus confirming the accuracy of the measurement system and the estimation of the convective heat release rate from the buoyancy source.

It can be seen in Fig. 2 that above the heat source the fluid rapidly accelerates to a high velocity over a short distance and then starts to decelerate. The effect of grid refinement on centreline velocities is shown in the same figure. Very fine calculation grids are needed for grid independent results. A failure to provide enough mesh in the plume will result in the plume flow being insufficiently resolved, so that the momentum is rapidly and artificially diffused causing too low centreline velocities near the heat source. It can be estimated from the axisymmetric calculations that in three dimensions the denser grid should be more than doubled in each direction to achieve grid independent results. This means that the number of cells required is about seventeen times the number of cells used in this study, thus highlighting the substantial computing requirements demanded by a combined analysis of this type flow.

It is also seen in Figure 2 that the k-e model overpredicts the plume centreline velocities. When the standard value CM=0.09 and default value PrT=0.7 were used, the calculated velocities in the decay region were 20 % higher than those obtained experimentally. The velocity profile was also narrower than the measured one. With the optimized values CM=0.11 and Pr-,^0.85 the velocities were overpredicted by 10

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W (m

s-1)

% and the velocity profile widhts were similar to LDA measurements and previous observations (Shabbir and George, 1994).

W = 3.3 (

MEASURED

AXISYMMETR1C 62x32 RECTANGULAR 62x32x62 AXISYMMETRIC 82x42 AXISYMMETRIC 162x82 AXISYMMETRIC 322x162

Figure 2. Predicted and measured mean velocity along the axis of a pure plume.

A curve fit of the measured velocities along the plume axis defines a virtual origin for the mean centreline velocity at approximately 0.5 diameters above the top of the heat source. The curve fit is plotted in Fig. 2 with a dashed line. The results suggest that equation 8 is valid from about two heat source diameters downstream from the top of the heat source.

The predicted behaviour of the plume near the exhaust opening is illustrated in Fig 3, where constant density contours are plotted for two exhaust flow rates. With the lower exhaust flow rate the plume is somewhat bent towards the hood but continues to rise. As the exhaust flow rate is increased, the plume becomes fully captured.

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a) b)Figure 3. Predicted contours of constant density.

The measured and the predicted mean vertical velocities on the hood centreline with three different exhaust flow rates of 0.032 mV1, 0.066 rri s' and 0.10 ihi are shown in Figure 4. These flow rates correspond to the measured average capture efficiencies of 10, 64 and 98 %, respectively. The vertical velocity profiles on the hood centreline show clearly the effect of increasing suction on the plume trajectory. With the lower exhaust flow rate the plume velocity is high compared to the velocities created by the exhaust hood and the plume seems to escape. This was confirmed also by the tracer gas measurements. With the higher exhaust air flow rates the plume deflects towards the hood, which can be seen from the vertical velocities. The maximum vertical velocity decreases and its location moves towards the hood face as the exhaust flow rate increases (Fig. 4). The calculations with the finer grid gave somewhat higher vertical velocities in the plume region.

The horizontal centreline velocities were calculated fairly well. An example of the predicted and measured centreline velocities is in Fig. 5. There was not much difference between the results obtained from the two different calculation grids. The relatively largest deviations were observed near the heat source, where the scatter in the measured mean velocities was also large.

When an exhaust opening is drawing air from still air the turbulence does not significantly affect the mean flow, which is essentially inviscid. However, when

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exhausting near a hot contaminant source the buoyant plume generates high turbulence, which is connected with the mean flow. Turbulence affects the dispersion of contaminants and the momentum and therefore its proper prediction is essential for accurate calculations.

q = 0.032 m3 s'1

0.20 m

E 0.5• MEASURED

------- GRID 32x21 x 36..........GRID 62x32x62

a)

q le = 0.066 m3 s'1

10/12

0.9

q le = 0.10 m3 s'1

0.20 m

E 0.4

• • •

• MEASURED------ GRID 32x21 x 36

GRID 62x32x62

0 0.05 0.1 0.15 0.2 0.25x (m)

Figure 4. Predicted and measured mean vertical velocity profiles on the hood centreline with three different exhaust flow rates.

q le = 0.066 m3 s'1

0.20 m

=> 1.5

• MEASURED— GRID 32x21 x 36— GRID 62 x 32 x 62

Figure 5. Predicted and measured mean horizontal velocities on the hood centreline.

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The calculated and the measured normal stresses in Figures 6 and 7 illustrate the variations in the turbulence on the hood centreline with two different exhaust flow rates. In the plume region far from the exhaust opening the turbulence production is due to shear stresses and buoyancy production, while near the exhaust opening the turbulence production is mainly due to normal stress. The measured vertical velocity fluctuations were clearly higher than the horizontal ones (Figure 6). Here the calculations underestimated the measured normal Reynolds stress components u2 and w2 (Figure 6). This may result in an underestimation of the contaminant dispersion in the plume region.

q le = 0.032 m3 s"1

Calculated w:

Calculated u2

ODD'

• Measured w2 a Measured u2

Figure 6. Predicted and measured normal stresses on the hood centreline with an exhaust flow rate of0.032 m3 s'1.

When the flow along the hood centreline is accelerated towards the opening, the streamwise fluctuations decrease, while the cross-stream component increases (Fig. 7). Experiments with the other exhaust flow rates showed, that the lateral velocity fluctuations increase with the hood face velocity. This is similar to observations in wind tunnel contraction sections and is likely caused by a strong streamwise velocity gradient stretching vortex filaments in the streamwise direction and contracting them in the perpendicular directions. An increase in the cross-stream turbulence can be important in contaminant dispersion, especially for LVHV (Low Volume High Velocity) hoods, where very high velocity gradients occur near the exhaust opening. It may thus be anticipated that for highly turbulent flows a hood

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with small face area is less effective in controlling contaminants than a large hood with an equal exhaust flow rate. However, more research is needed to verify this.

q le = 0.10 m3 s'1

Calculated w:

Calculated u2

x (m)

• Measured w2 □ Measured u2

Figure 7. Predicted and measured normal stresses on the hood centreline with an exhaust flow rate of 0.10 m3 s’.

In the k-e turbulence model the normal stresses are calculated by

3 “dx= — k - 2v

3dW’dz (9)

As Figure 7 shows, the k-e model does not predict the normal stresses well when the flow approaches the hood opening. The streamwise fluctuations are underestimated and the cross-stream component overestimated. This is because of the overprediction of kinetic energy production and the kinetic energy near the hood face. This discrepancy can be attributed to the k-e model's inadequacy to calculate accurately flows in the regions where the production of turbulence is governed by normal stresses (Taulbee and Tran, 1988). The overestimation of turbulent kinetic energy k leads to large eddy viscosity vT. Near the hood face the velocity gradient dU/dx is also large and positive so that negative normal stress u1 would result, which is unrealistic. On the other hand, the vertical velocity gradient dW/dz on the

10/15

hood centreline is negative so that the calculated cross stream component w1 becomes very large.

The experimental and the calculated capture efficiencies are shown in Fig. 8. The standard deviations of the measured efficiencies are indicated by vertical bars. Capture efficiency depends on both separation distance and exhaust flow rate, as expected. The predicted capture efficiencies were clearly higher than measured. The calculations gave exhaust flow rates which were 40 - 50 % lower than what was actually required for an efficient contaminant control. It is difficult to say whether the discrepancies were due to the underprediction of the turbulence intensities in the plume region, resulting in underestimation of the contaminant dispersion, or due to the failure to obtain grid independent solution. Another reason for the rather poor capture efficiency predictions may be that in the simulations no disturbances were assumed at the freestream boundaries. In reality, the ambient air currents in the test room may have reduced the efficiency. However, confirmation of these results awaits finer grid solutions.

EXHAUST FLOW RATE (m3 s1)

q

□

MEASURED

O x=20 cm □ x=25 cm a x=30 cm

CALCULATED

• x=20 cm ■ x=25 cm ▲ x=30 cm

Figure 8. Predicted and measured capture efficiencies.

10/16

On the whole, although the simulations failed to predict the turbulent fluctuations in the plume region or the capture efficiencies very well, the mean velocities were calculated with reasonable accuracy. The source-hood interaction is a complex flow case and requires large computer resources for its proper prediction. However, this information is necessary when designing efficient local exhaust ventilation systems for buoyant contaminant sources and is difficult to obtain by other means.

Acknowledgements. This work was financially supported by the Finnish Technology Development Centre (TEKES) and by the Finnish Work Environment Fund (TSR).

REFERENCES

Bender, M. (1979) Fume hoods, open canopy type - their ability to capture pollutants in various environments. Am. ind. Hyg. Ass. J. 40, 118-127.

Cesta, T. (1989) Capture of pollutants from a buoyant point source using a lateral exhaust hood with and without assistance from an air curtain. In Ventilation '88 (Edited by Vincent, J.) pp. 63-79. Supplement to The Ann. occup. Hyg.

Chen, C.J. and Chen, C.H. (1979) On prediction and unified correlation for decay of vertical buoyant jets. ASME Journal of Heat Transfer 101, 532-537.

Davidson, L. (1990) Second-order corrections of the k-e model to account for nonisotropic effects due to buoyancy. Int. J. Heat Mass Transfer 33, 2599-2608.

Kulmala, I. and Saarenrinne, P. (1996). Air flow near an unflanged rectangular exhaust opening. Energy and Buildings 24, 133-136.

Madni, I.K. and Fletcher, R.H. (1977) Prediction of turbulent forced plumes issuing vertically into stratified or uniform ambients. ASME Journal of Heat Transfer 99, 99-104.

Malin, M R. and Younis, B.A. (1990) Calculation of turbulent buoyant plumes with a Reynolds stress and heat flux transport closure. Int. J. Heat Mass Transfer 33, 2247-2264.

Ogino, F., Takeuchi, H., Kudo, I. and Mizushina, T. (1980) Heated Jet discharged vertically into ambients of uniform and linear temperature profiles. Int. J. Heat Mass Transfer 23, 1581-1588.

Papanicolaou, P.N. and List, E.J. (1988) Investigations of round vertical turbulent buoyant jets. /. Fluid Mech. 195, 341-391.

Rodi, W. (1984) Turbulence Models and Their Applications in Hydraulics. International Association for Hydraulic Research, Delft.

Rouse, H. Yih, C.S. and Humphreys, H.W. (1952) Gravitational convection from a boundary source. Tellus 4, 201-210.

Shabbir, A. and George, W. (1994) Experiments on a round turbulent buoyant plume. J. Fluid Mech. 275, 1-32.

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Shabbir, A. and Taulbee, D.B. (1990) Evaluation of turbulence models for predicting buoyant flows. Journal of Heat Transfer 112, 945-951.

Taulbee and Tran (1988) Stagnation streamline turbulence. A1AA Journal 26, 1011- 1013.

Turn Suden, K.D., Flynn, M. R. and Goodman, R. (1990) Computer simulation in the design of local exhaust hoods for shielded metal arc welding. Am. ind. Hyg. Ass. 7. 51,115-126.

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Reprinted with permission from the publisher.In: American Industrial Hygiene Association Journal 1996. Vol. 57, April, pp. 356 - 364.

Paper 11

Authors

Kimmo Heinonen” Ilpo Kulmalab Arto Saamanen1

aVTT Manufacturing Technology, Safety Engineering, P.O. Box 1701, FIN-33101 Tampere, Finland; Tampere University of Technology. Energy and Process Engineering, P.O. Box 589, 33101 Tampere, Finland; On leave from VTT Manufacturing Technology Tampere, Finland

Local Ventilation For Powder Handling—Combination of Local Supply and Exhaust Air

The performance of a modified local ventilation unit equipped with local supply and exhaust ventilation was evaluated during the manual handling of flour additive powder.The investigation tested five different configurations to study the effects of the exhaust opening location and local supply air on worker exposure.The measurements were done under controlled conditions in a test room.The breathing zone (BZ) dust concentration was measured by gravimetric sampling and real time monitoring.The different local ventilation configurations were also modeled numerically using computational fluid dynamics. Without local ventilation the average BZ dust concentration was 42 mg/m3. With local exhaust only the exposure was reduced below 1 mg/m3.The addition of local supply air further reduced the exposure to below 0.5 mg/m3.The lowest results were achieved by locating two exhaust openings on either side

of the contaminant source combined with local supply air. With this configuration the average BZ exposure was only 0.08 mg/m3,a reduction of 99.8%. Numerical simulations also gave useful information about the airflow fields in stationary conditions. However, the worker's exposure was greatly affected by body movements, and this was not possible to simulate numerically.The results of this investigation can be useful when controlling dust exposure in manual powder handling operations.Keywords: computational fluid dynamics, dust control, local ventilation, manual

powder handling

Manual powder handling often causes overly high exposures to harmful substances, which may result in a health hazard. An example is bakeries, where the increased prevalence of respiratory symptoms

such as asthma and rhinitis is common among workers/3"33 Recent studies have related these problems largely to enzyme-containing flour additives. The strongest sensitizer reported is a- amvlase, which is added to baking flours to improve the rising of the dough/11 However, only a few measurements of a-amylase concentrations in the baking industry have been published in the literature. The highest exposures to a-amylase have been reported to be during the manual handling of powdered bread improver when mixing,

This work was financially Supported by The Finnish Work Environment Fund and Finnish Tech: nolog)- Development Centre.

packing/21 and weighing flour additives/11 During manual weighing the measured mean a-amylase concentration was 7.3 pg/m5/11 The current American Conference of Governmental Industrial Hygienists (ACGIH) threshold limit value (TLV®j ceiling value for subtiiisins is 0.06 pg/m3/4' but it is not known if this TLV also is applicable to nonproteolvtic enzymes like a-amylase. However, because the present body of knowledge does not permit the setting of a NOAEL (no observable adverse effect level) for any industrial enzyme,131 the exposure should be controlled as effectively as possible.

Local exhaust ventilation is widely used to remove contaminants at the point of generation and thus prevent contaminants from entering the worker’s breathing zone. Recently, local supply air also has been successfully used in combination with local exhaust to further reduce the exposure by providing a region of clean air around the worker/3"8’ Information on the design of local

exhaust ventilation for manual powder handling can be found in the literature.''1-10' However, little information is available to quantify the reduction in worker exposure.181 Moreover, the instructions generally deal with physical hood designs and exhaust airflow rates; they do not provide much information on the use of supplemental local supply air.

Transport of airborne particles, and thus exposure potential, depends on the air movements near the worker and exhaust openings. Therefore, it is essential to be able to predict the airflow fields accurately. This is difficult because the equations describing turbulent airflow are complex, and conventional solutions are impractical. However, in the past two decades, because of developments in computer technology and computational techniques, computer-aided solutions to flow equations have become more- feasible. Nevertheless, despite these potential benefits, computational fluid dynamics (CFD) is rarely used for modeling local ventilation flows.'11"18

In this study CFD modeling was used to investigate the effects of the locations of the local exhaust opening and local supply air on the airflow fields of a local ventilation unit. The efficiency of the local ventilation unit during manual powder handling was determined in laboratory experiments for a variety of configurations.'16' In the experiments the control efficiency was assessed by measuring the worker’s breathing zone dust concentration. The predictions were then compared with the experimental measurements, and on the basis of the results the optimum control configuration was determined.

Numerical Simulations

The modified local ventilation unit used in this study (Comfo LCI 1000, Halton Co., Finland) was modeled numerically using the FLUENT (version 3.02) CFD computer code. The ventilation

unit was equipped with local supply and exhaust ventilation. The purpose of the supply air was to provide vertical airflow of clean air to aid in the control of airborne contaminants. In a normal operating condition the supply air is introduced through a 0.8-m X 1.0-m perforated plenum, and the exhaust air exits through a sidedraft slot of 0.1 m x 1 m.

In the modeling of the local ventilation unit, a three-dimensional rectangular calculation grid 35 X 24 X 35 was used, as shown in Figure 1. The grid had stepped sides at the inclined front wall, but because the flow accelerated at that point, the approximate geometry had little impact on the flow predictions. Only half of the flow field was modeled because of the vertical symmetry. Uniform velocity was assumed at the exhaust openings and at the supply inlet, and constant pressure at the freestream boundaries.

A previous study demonstrated the applicability of the CFD simulations for modeling the local ventilation unit. Previously, the airflow and the concentration fields were calculated for a sidedraft exhaust hood with local supply air.1151 In this study the airflow fields were calculated in five different cases: (1) a downdraft hood between the worker and the working table (Case 2); (2) a sidedraft hood at the opposite side of the working table (Case 3); (3) a downdraft hood in combination with local supply air (Case 4); (4) a sidedraft hood in combination with local supply air (Case 5); and (5) sidedraft and downdraft hoods in combination with local supply air (Case 6).

Case 1 was the situation with dilution ventilation only and was not modeled. The local supply and exhaust flow rates in the CFD simulations were the same as those used in the experimental measurements (Table I).

The airflow fields were calculated by numerically solving the continuity and Reynolds equations describing isothermal steady- state fluid flow. These equations can be written using tensor notation as

, SUi' 9x

au,ax, = o

ap a /au; au.ax. pUiUj

CD

<2)

where U, is the mean and u, the fluctuating velocity component in the direction x„ P is the mean pressure, p is the fluid density, and u is the viscosity. The last term on the right side of Equation 2 is the gradient of turbulent stresses, known as the Reynolds stresses, which arise due to velocity fluctuations. An appropriate turbulence model is needed to express these stresses in terms of either known or calculable quantities. In this study the standard k-e turbulence model was used, in which the Reynolds stresses arc modeled according to:

where 8,, is the Kronecker delta, and p, is the turbulent viscosity. This depends on the local state of turbulence. In the k-E model it is calculated bv:

C„p ^k2

(4)

where C„=0.09. The turbulence kinetic energy k and its dissipation rate e are solved from their modeled forms of transport equa tions.11"1

The quadratic upstream interpolation (QUICK)1181 scheme was used for the discretization of the convective terms, and the SIMPLE solution algorithm was used to solve the linearized equations.1191 Sufficient convergence was assumed to be reached when the sum of successive fractional changes (residuals) was less than 10"’. A solution for the three-dimensional velocity field required about 10 hr of CPU time on a Sun Spark Server 690 MP.

Laboratory Measurements

The effect of local ventilation was studied during the simulated manual weighing of flour additive powder. The exposure measurements were conducted in a test room with a floor area of 4.8 no

X 3.6 m and a ceiling height of 3.6 m (Figure 2). The general ventilation supply air for the test room was introduced through ceiling- mounted low-velocity diffusers, and the extraction was from a grille in the wall at ceiling level. The modified local ventilation unit was installed near a wall in the test room and was equipped with its own supply and exhaust ventilation. In addition, a 0.05-m X 1-m downdraft slot hood was installed between the worker and the working table. During the tests the sum of the local and general exhaust flow rates was held at a constant value of 0.4 m’/sec, corresponding to an air exchange rate of 23 hr-1 (nominal time constant t=2.6 min). The airflow rates were measured by ISA 1932 nozzles. The supply- air was HEPA-filtered to minimize the influence of background concentrations on the results.

The inlet of the local supply air unit was 2.0 m above the floor. To achieve a more uniform velocity distribution below the supply

11/2

FIGURE 1. Calculation grid and dimensions for the local ventilation unit

air unit, a fabric felt filter was attached downstream of the perforated plate.1'1’1

The experiments tested the same configurations that were studied in the CFD simulations. To establish a baseline exposure without local exhaust, the measurements were conducted with only the general room ventilation in operation. Table I lists the cases and the corresponding airflow rates. The supply air for the general and local ventilation was isothermal in all the cases.

It was necessary to standardize the work tasks to minimize variation for each experiment. In every experiment the same worker scooped the flour additive powder from one container beside the worker into another on the working table. The top of the container (height and diameter 0.28 m) was situated beside the worker at table level. The receiving container (height 0.11 m and diameter 0.3 m) was situated in the center of the table. The worker scooped small quantities of the flour additive powder (approximately 40 g) and sprinkled it in the receiving container at 5-second intervals. Once during each test the receiving container was filled, and replaced with an empty one. The amount of scooped powder in each experiment was 6.8 kg.

The worker’s dust exposures were determined by standard gravimetric filter sampling and by real-time monitoring. The dustiness index of the flour additive powder was relatively high.

| Studied Configurations

Local Exhaust Flow Rate (mVsec)

Local Supply Flow Rate

Case Downdraft Sidedraft (mVsec) Supply Exhaust Mean SD

1 0 0 1 0 0.40 0.40 42 7.42 0.20 0 0 0.40 0.20 0.7 0.293 0 0.20 0 0.40 0.20 0.8 0.454 0.20 0 0.14 0.26 0.20 0.2 0.145 0 020 0.14 0.26 0.20 0.3 0.236 0.10 0.10 0.14 0.26 0.20 0.08 0.05

The measured MRI-indcx was about 100 mg/kg, compared with about 5 mg/kg for wheat flour. Thus, it was possible to produce measurable dust concentrations even when local ventilation was used. The dust sampling filter cassettes were attached to the worker’s left lapel. Depending on the filter load samples were collected on open-faced polycarbonate (Nu- cleporc 0.4 um pore size) or cellulose ester (Millipore 0.8 um pore size) 37-mrn filters. Cellulose ester filters were used when there was no local ventilation and the BZ dust concentrations were high. With local ventilation the concentrations were lower, and polycarbonate filters were used because of their better weight stability. To collect measurable quantities of dust within a reasonable

time, the sampling was done at 19 L/min. The sampling filters were connected with PVC tubing to a floor-mounted pump. After 24 hr of desiccation both the samples and three blank filters were weighed using an electrobalance.

Real-time dust monitoring used a portable aerosol photometer (Miniram model PDM-3) attached to the worker’s right lapel. The photometer’s analog output was recorded at I -second intervals with a data logger connected to a personal computer for data analysis.

Each experiment lasted 15 minutes. To obtain steady-state dust concentrations the sampling commenced 5 minutes after the start of the transfer activity. Each case was tested five times in mixed orders, and the test room was carefully vacuum-cleaned between runs.

RESULTS

Figures 3-7 contain the calculated air-velocity fields. The predicted air velocities in the symmetrical plane depended on the configura

tion. In the case of the downdraft hood the exhaust resembled a line sink, and the constant velocity contours could be approximated by

three quarters of a cylinder, since air entered the slot through an effective 270° arc (Figure 3). With the sidedraft exhaust the front wall of the local ventilation unit and the working table acted as flanking planes, and the velocities around the receiving container were increased significantly compared with the downdraft hood (Figure 4).

As shown in Figures 3-6, the local supply air had little effect on the airflow fields near

General Ventilation Flow Rate (mVsec)

bustConcentration

(mg/m3)

11/3

LOCAL EXHAUST LOCAL SUPPLT A:R

FIGURE 2.The test room and the local ventilation unit

the exhaust openings. The velocity contours down to 0.5 m/sec were almost unchanged. On the other hand, local supply air created a downward airflow, and this made velocities farther away from the exhaust opening decrease more slowly than they would without the local supply air (Figures 5 and 6). The CFD calculations were done in unobstructed conditions, and it is probable that the worker and the container on the table would cause some distortion on the predicted airflow fields.

CASE 3

0.1 m/s

1.5 m

FIGURE 4. Predicted velocity contours in the vertical symmetry plane with the sidedraft hood

CASE 2

0.5 0.3

0.1 m/s

1.5 m

FIGURE 3. Predicted velocity contours in the vertical symmetry plane with the downdraft hood. The location of the receiving container on the table is indicated by dashed lines.

CASE 4

0.1m/s0.3 n.7

1.5 mFIGURE 5. Predicted velocity contours in the vertical symmetry plane with local supply air and the downdraft hood

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CASE 5

2.0 -

0.1 m/s

1.5 m

FIGURE 6. Predicted velocity contours in the vertical symmetry plane with local supply air and the sidedraft hood

Figure 8 and Table I contain the dust concentrations in the worker’s breathing zone in the test cases. The figure shows the arithmetic mean breathing zone concentration (C) and the standard deviation (o) of the measurements. The vertical bar indicates the relative mean concentration.

With the room general ventilation only, the dust concentration was 42 mg/m3. The addition of local exhaust ventilation alone reduced the mean concentration to below 1 mg/m3. The exposure was further reduced by the addition of local supply air. The lowest BZ exposure was obtained with both the sidedraft and the downdraft exhausts in combination with local supply air. With this configuration the BZ dust exposure was only 0.08 mg/m5, corresponding to a reduction of 99.8% over general ventilation alone.

To find out the statistical differences in the worker’s exposure among the various ventilation arrangements, a single factor analysis of variance and Duncan’s multiple range test were done. Before the data analysis, variances were stabilized by logarithmic transformation of the BZ concentrations. Concentrations lower than the detection limit (0.08 mg/m3) were replaced with the value of half of the detection limit. As seen in Table II, the ventilation systems differed significantly. Multiple comparisons between the averages of different cases were done using Duncan’s test. Table III presents the homogenous subsets of ventilation systems, in which the log- transformed averages do not differ from each other at the 0.01 significance level. Four different subsets were formed that differed significantly from each other. High BZ exposure in dilution ventilation (Case 1) produced Subset 1. Subset 2 included Cases 2 and 3, systems with local exhaust ventilation alone. Cases 4 and 5, one exhaust combined with local supply air, formed Subset 3. Case 6, exhaust from two locations with local supply air, resulted in the lowest BZ exposure and formed Subset 4.

The gravimetric concentrations correlated quite well with the average output voltage of the photometer during each local ventilation test run. Although there were some differences between the two sets of analyses, the real-time data gave similar relative differences for the various local ventilation configurations, as did the gravimetric sampling.

Discussion

In this study the effects of the location of the local exhaust inlet and use of local supply air on the efficiency of a local ventilation

unit were investigated both numerically and experimentally. The experiments showed that using only local exhaust ventilation, the BZ dust concentration could be considerably decreased. With the exhaust either from the sidedraft or from the downdraft inlet, the mean concentration was 98% below the BZ dust concentration measured with only the general ventilation.

According to the numerical predictions, local supply air creates a downward airflow pattern that directs contaminants away from the BZ and thus may improve worker protection (Figures S and 6). This was also confirmed by the measurements, in which the combination of supply and local exhaust resulted in a further decrease in exposure. As with the local exhaust alone, there was no statistically significant difference in exposure reduction between the two exhaust locations.

Because the predicted velocities around the container were clearly higher with the sidedraft hood (Figures 3-6), one would expect that the control efficiency of the sidedraft hood would also have been better. Even though the capture efficiency with the sidedraft hood may have been greater than with the downdraft hood, the measured mean BZ concentrations were about the same.

CASE 6

1.5mFIGURE 7. Predicted velocity contours in the vertical symmetry plane with local supply air and both the sidedraft and the downdraft hoods

11/5

CASE 4CASE 1

C = 42 mg/m3, a = 7.4 mg/m3

CASE 2

0.2 m3/s

CASES

l 0.14 m3/s ~~) 0.2 m3/s

x\\'s\-XVx<<x<.

C = 0.2 mg/m3, o = 0.14 mg/m3

CASES

\ ■ ' x \ x x \ \\ x \ \ x x

C = 0.3 mg/m3, a = 0.23 mg/m3

CASE 6

. 0.14 m3/s J 0.2 m3/s O O O

C = 0.08 mg/m3, a = 0.05 mg/m3C = 0.8 mg/m3, o = 0.45 mg/m3

FIGURE 8. Measured dust concentrations in the worker's breathing zone with different configurations

11/6

CW3CTH One Way Analysis of Variance on the Log-Transformed Breathing Zone ConcentrationsSource of Variance OF*

Sum of Squares

MeanSquares F Ratio P

Ventilationcase 5 131.8821 26.3764 85.0362 <0.0001

Error 24 7.4443 0.3102Total 29 139.3264

A0F = degree of freedom

The best results were clearly achieved when both exhaust inlets were used in combination with local supply air. With this configuration the predicted velocities around the receiving container were lower than with the sidedraft hood, but higher than with the downdraft hood. The exposure was below 0.2% of the BZ concentration from the dilution ventilation alone. Interestingly, this reduction was obtained without increasing the exhaust airflow rate.

During the experiments dust was mainly generated by strewing the flour additive powder into the receiving container. According to the real-time monitoring data, the exposure was a series of peaks (Figure 9). It is possible that the worker’s movements induced turbulent air currents that caused the contaminated air to move from the receiving container into the worker’s breathing zone. It is assumed that this dust-laden air was captured by the downdraft hood between the worker and the working table. The findings suggest that by dividing the exhaust into two inlets, the contaminants generated during the pouring operation were captured quite effectively by the sidedraft hood, and that the escaping dust traveling toward the worker was in turn controlled by the downdraft inlet and kept away from the BZ by the vertically flowing supply air.

The calculated velocities at the contaminant source were quite low (<0.1—0.5 m/sec) compared with the commonly recommended capture velocities (0.5-1.0 m/sec).'101 On the other hand, the working table and the inclined front wall, together with the side walls, partly enclosed the work area and thus reduced the effect of disturbing airflows on capture efficiency.

The measurements are consistent with the previous findings suggesting that local supply air can be used to reduce worker exposure.'5-8'20-”1 The average supply air velocity in this study was only about 0.2 m/sec, whereas in previous studies it was on the order 0.14-1.9 m/sec.'5"8-20-221 High velocities and velocity fluctua-

Homogeneous Ventilation System Subsets According to the Duncan's Multiple Range Test with Significance Level 0.01 on the log Transformed Breathing Zone Concentrations

Homogeneous Subsets’

Subset 1 ventilation system Case 1

mean 3.735Subset 2 ventilation system Case 2 Case 3

mean -0.364 -0.360Subset 3 ventilation system Case 4 Case 5

mean -1.600 -1.583Subset 4 ventilation system Case 6

mean -2.954

^Highest and lowest means are not significantly different

tions can cause discomfort by producing draughts.'231 Therefore, better thermal comfort is obtained with lower air velocities and turbulence intensities. On the other hand, lower velocities may be more susceptible to the momentum of the contaminant source, cross drafts, and other disturbances. In this study the local supply air was isothermal. Previous studies have indicated that using cooler supply air than ambient air may improve worker protection.'32'-221 This is because the buoyancy force, which acts on a vertically flowing supply air of lower temperature from the surroundings, assists the inertia forces and increases the momentum of the supply air. Therefore, cooler supply air reaches the worker’s breathing zone better than isothermal air.

Air velocity patterns near unobstructed exhaust hoods are described fairly accurately by solutions based on potential flow theory.'24-271 This implies that in these cases the flow can be assumed to be in viscid. It can be concluded that in the flows with only local exhaust, the relative importance of the turbulent and viscous stresses outside the thin boundary layers near surfaces are negligible. Consequently, the inertial terms on the left side of Equation 2 are balanced mainly by the pressure gradient. Therefore, it is not surprising that the airflow fields near exhaust openings can be predicted quite well with CFD simulations,'13'141 and that the choice of the turbulence model appears to have little effect on the predicted flow fields except in the immediate vicinity of the exhaust opening.'281

When local supply air is used, downward-flowing clean air is mixed with ambient air below the local supply air unit in a free mix

ing layer. In this layer, turbulent stresses are important, and the accuracy of the simulations depends on the performance of the turbulence model. In the mixing layer, velocity and concentration fields can be predicted reasonably well with the k-e model, provided that the supply air velocity is uniform.'151 When more complex cases are solved, such as strongly buoyant flows or flows with strong streamline curvature, more sophisticated turbulence models may be needed for accurate solutions.

The present design practice for local exhaust ventilation is

SIDE DRAFT-t-SUPPLY AIR

SO 100 150 200TIME (s)

FIGURE 9. Examples of the relative dust concentration variations in the breathing zone with different configurations. An output of 10 mV corresponds approximately to concentration of 2 mg/m1.

11/7

to select an appropriate hood type and the necessary capture or control velocity. Based on this the required exhaust airflow rate is determined. In general, this depends on the distance between the contaminant source and the exhaust opening and on the hood geometry. Due to the difficulties in calculating airflow fields the velocity calculations are usually limited to determining centerline velocities. While useful, this method does not take into consideration parameters that affect the efficiency of local ventilation systems. These include cross draft velocity, turbulence and direction, and contaminant source. Source issues include release rate, velocity and direction, heat release rate, and in the case of particulates, particle size distribution. These effects often can be conveniently simulated using numerical calculations. However, the results of this study also revealed that the worker’s movements may strongly influence the exposure level. To describe these effects, the time- dependent flow should be solved. However, these calculations in three dimensions would require impractically long and expensive calculations on available computers. Therefore, experimental methods are still needed in complex local ventilation studies. Nevertheless, numerical steady-state simulations are helpful in providing better understanding of airflows, and they can help in designing more efficient local ventilation systems.

As the test results showed, a very significant exposure reduction can be achieved using local ventilation in manual powder handling. Because no TLV exists for cc-amylase, and because the substance is a potential sensitizer, it is necessary to control exposures to as low as is feasible during the handling of enzyme- containing additive powders in bakeries. Thus, on the basis of the results the recommended configuration is to use local supply air in combination with sidedraft and downdraft exhaust openings to control the airborne dust. In field installation the effectiveness of any engineering control should be verified by exposure monitoring.

These results may also be applied to other isothermal dust-generating situations during powder handling, such as mixing and packing. The use of local supply air with local exhaust may also improve worker protection with gaseous contaminants, but additional studies are needed to verifV this.

Conclusions

Local exhaust ventilation reduced the worker’s exposure greatly during manual powder handling. The use of local supply air in combination with the local exhaust further decreased the expo

sure. The best results were achieved by locating two exhaust openings, a sidedraft and a downdraft, on both sides of the contaminant source in combination with the local supply air. It is recommended that one of the exhaust openings be situated between the worker and the contaminant source. More research is needed to determine the exposure reduction in actual operating conditions.

The present design practice of local ventilation systems is often based on the capture velocity and centerline velocity formulas. Nevertheless, knowledge of larger velocity fields is often required or at least desirable. These velocities can be conveniently calculated with CFD simulations. Cautiously used and interpreted, these CFD simulations can offer a significant benefit in optimizing local ventilation systems. As the performance of computers increases, more complex situations can be modeled. In any case, the effects of worker movements on the capture efficiency and exposure reduction may be difficult to accurately predict.

ACKNOWLEDGMENTS

Halton Company is thanked for the loan of the local ventilation unit.

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Published byVuorimiehentie 5, P.O.Box 2000, FIN-02044 VTT, Finland Phone internal.+ 358 9 4561

VII Fax + 358 9 456 4374

Name of project

INVENT

Commissioned byTechnology Development Centre (TEKES), Jenny and Antti Vihuri foundation

Title


Abstract

Local ventilation is widely used in industry for controlling airborne contaminants. However, the present design practices of local ventilation systems are mainly based on empirical equations and do not take quantitatively into account the various factors affecting the performance of these systems. The aim of this study was to determine the applicability and limitations of more advanced fluid mechanical methods to the design and development of local ventilation systems. The most important factors affecting the performance of local ventilation systems were determined and their effect was studied in a systematic manner. The numerical calculations were made with the FLUENT computer code and they were verified by laboratory experiments, previous measurements or analytical solutions.The results proved that the numerical calculations can provide a realistic simulation of exhaust openings, effects of ambient air flows and wake regions. The experiences with the low-velocity local supply air showed that these systems can also be modelled fairly well. The results were used to improve the efficiency and thermal comfort of a local ventilation unit and to increase the effective control range of exhaust hoods.In the simulation of the interaction of a hot buoyant source and local exhaust, the predicted capture efficiencies were clearly higher than those observed experimentally. The deviations between measurements and non-isothermal flow calculations may have partly been caused by the inability to achieve grid independent solutions.CFD simulations is an advanced and flexible tool for designing and developing local ventilation. The simulations can provide insight into the time-averaged flow field which may assist us in understanding the observed phenomena and to explain experimental results. However, for successful calculations the applicability and limitations of the models must be known.

Activity unitVTT Manufacturing Technology, Safety Engineering, Tekniikankatu 1, P.O.Box 1701, FIN-33101 TAMPERE, Finland

ISSN and series title1235-0621 VTT PUBLICATIONS

ISBN Language

951-38-5052-8 English

Class (UDC)697.9:658.382

Keywordsventilation, indoor air, air flow, exhaust systems, gas dynamics

Sold by VTT Information ServiceP.O. Box 2000, FIN-02044 VTT, FinlandPhone internal. + 358 9 456 4404Fax + 358 9 456 4374

Pages80 p. + app. Hip.

Price groupD

Author(s)

Kulmala, Ilpo

Series title, number and report code of publication

VTT Publications 307 VTT-PUBS-307

Date Project numberApril 1997

Advanced design of local ventilation systems

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