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FORM 836 (10/96)

LA-UR-99-5968Approved for public release;distribution is unlimited.

Title:Implications of Room Ventilation andContainment Design for Minimization ofWorker Exposure to Plutonium Aerosols

Author(s): Jeff Whicker, John Rodgers, Piotr Wasiolek, CurttAmmerman, Ricky Lopez, and Murray Moore

Submitted to:

http://lib-www.lanl.gov/la-pubs/00460116.pdf

Implications of Room Ventilation and Containment Design forMinimization of Worker Exposure to Plutonium Aerosols

Co-investigators

Jeff Whicker, ESH-4, Health Physics MeasurementsJohn Rodgers, ESH-4, Health Physics Measurements

Piotr Wasiolek, ESH-4/NMIT, Long-term visiting scientistCurtt Ammerman, ESA-DE, Design Engineering

Ricky Lopez, ESH-5, Industrial HygieneMurray Moore, ESH-4, Health Physics Measurements

FundingFY 98: $42 KFY 99: $82 K

1999 Annual Progress Report

IntroductionIn many work environments where toxic or radioactive materials are handled

there is always a possibility of accidental airborne releases of toxic or radioactiveaerosols or gases. This requires that safety professionals and engineers design effectivewarning systems and countermeasures to minimize a worker’s risk. Computersimulations through computational fluid dynamics (CFD) modeling of air flows andaerosol transport, combined with tracer experiments can provide critical information fordetermining where to place early warning and monitoring instruments, and how tominimize hazardous materials in the worker’s breathing zone.

The amount of a toxin inhaled by a worker depends on the temporal and spatialdispersion patterns in the rooms, time-dependent concentrations in the worker’s breathingzone, and the achieved level of protection from alarming air monitors. Aerosoldispersion patterns are driven by complex interactions of room ventilation rate anddesign, room furnishings, airflow characteristics, human presence and activity, andcharacteristics of the toxin (i.e., particle size, release rate, release location, etc.). Safetyprofessionals usually assume an instantaneous and perfectly uniform (mixed)concentration field when estimating exposures. This assumption can lead to largeunderestimates of exposure. For example, research has shown that complete mixing isoften not attained (Nicas 1996) or it can take up to several hours for complete mixing(Buchanan et al., 1995). In addition, steep, time-dependent concentration gradients canexist in the vicinity of the release, an area which often the worker(s) who caused therelease are within and could get large exposures (Dresher et al., 1997; Whicker et al.,1997).

Buchanan et al., (1995), also demonstrated that airflows can be significantlyaltered with the simple addition of a partition in a room, and that mixing improves as theairflow disruption increases. This disruption depended on the interplay of the obstructionsize, shape, and placement relative to convective flows. Nielsen (1998) showed theinfluence of furniture on air velocities in occupied areas, and that the influence seemedgreater at the higher room air exchange rates. Because in the LANL plutonium facilityglovebox sections can be added, removed, or modified, and ventilation rates canfluctuate, it is important to investigate how changes in these can influence general airflowcharacteristics and aerosol transport.

The goals of this study were to investigate changes in airflow characteristics suchas velocity and direction, turbulence intensity, and aerosol dispersion rate as affected bychanges in ventilation designs (rate and diffuser design), interior room furnishings, andhuman presence. Ultimately, strategies for enhanced worker protection could be realizedthrough better understanding and accurate prediction of transport of released aerosols asinfluenced by ventilation induced airflow patterns, containment structures, andinteractions with a worker positioned in front of a containment structure.

Materials and Methods

Experimental Room

The simulated plutonium workroom used in this study is a freestanding structurelocated within a larger building. The room is a modular metal-wall structure withdimensions of 6.1 x 4.8 x 2.4 m (V = 70.3 m3) and is furnished with two mockupglovebox lines and an overhead passbox (a sealed tunnel used for moving radioactivesamples between gloveboxes in a plutonium facility) inside. The gloveboxes made ofaluminized foam board were removable so three different configurations can be arranged:1) two full rows of gloveboxes and passbox (FB), 2) half of the gloveboxes removed andpassbox (HB), and 3) all gloveboxes and passbox removed (NB). Schematic cross-sections of the room configurations are presented in Figure 1a, b, and c.

The room is supplied with close-looped HEPA1-filtered air using a portableHEPA filtered blower 2with the incoming air passing through four 0.2 m-diameter inletnozzles with 0.3 m-diameter horizontal baffle plates that were located in the ceiling (seeFigure 1). Four 0.2 m-diameter adjustable flow exhaust registers are located in the roomcorners, 0.3 m above the floor. The nominal volumetric air exchange rate was set toapproximately 6 h-1 (LV-low ventilation) or 12 h-1 (HV-high ventilation) by adjusting thebaffle plate on the air-blower outlet line. Because the experimental room is locatedindoors with a thermally insulated floor, there was no significant (less than 0.5 oC)temperature gradient detected between opposite walls (including ceiling and floor), asmeasured with fine wire thermocouples3. The room openings (e.g., sampling or cableports) were sealed to make the structure as air tight as possible.

Air velocity measurementsA commercial sonic anemometer4 was used to characterize the airflow patterns.

Sonic anemometers measure the time-of-flight of pulsed sound waves across a 10-cmmeasurement path. To measure air velocity on each axis, two ultrasonic signals arepulsed in opposite directions and times-of-flight of the first signal (out) and second signal(back) are measured and air velocity calculated from the time difference. From thesemeasurements the three orthogonal air velocity components are determined with aprogrammable sampling rate that can be set from 1 to 60 Hz. A detailed description ofair velocity measurements in rooms using sonic anemometry is presented in Wasiolek etal. (1999).

The sonic anemometer head was mounted on a mobile cart for ease of transportand leveled after every change in sampling location. The mounting arrangement allowedfor changes in the sampling height. The sonic anemometer head (Vogt 1997) and themobile cart were designed to minimize local airflow disturbance.

Sampling frequency of the sonic anemometer was set to 1 Hz and data wascollected over a sampling interval of 600s. The raw, binary data files containing airvelocity individual components were converted to ASCII text format, corrected for offset, 1 High Efficiency Particulate Filter2 Model SP-700, Radiation Protection Systems, 10 Vista Dr, Old Lyme, CT 06371-15413 Model FW05, Campbell Scientific, Inc. Logan, UT, USA4 Model CSAT3, Campbell Scientific, Inc. , Logan, UT, USA

and rotated to align orientation of the sonic sampling head with common roomcoordinates.

By vector summation of individual air velocity vector components ux, uy and uz,the absolute air velocity was calculated for every sample, i, with the equation,

2zi

2yi

2xi

1i uuu)scm(u ++=− . (1)

The time average velocity for a 10-min run was calculated as =

=N

1iiu

N1u .

Turbulence MeasurementsA Statistical measure of the dispersion of data of a variable A about the mean A

is the unbiased variance 2Aσ defined as,

−=

=

−−

=σ1Ni

0i

2i

2A )AA(

1N1 . (2)

However, any turbulent variable A, can be split into mean and turbulent part as'aAA += , and the substitution of a turbulent part AA'a −= into the definition of

variance gives (Stull 1988),−=

=

=−

=σ1Ni

0i

22i

2A 'a)'a(

1N1 . (3)

Therefore, since the standard deviation is interpreted as a measure of the magnitude ofthe spread or dispersion of the original data from its mean, it can be used as a measure ofthe level of turbulence. The level of turbulence might be expected to depend on the meanwind speed, so it is often normalized to the air velocity. There are several definitions ofturbulence intensity used in the literature. Hanzawa et al. (1987) defined turbulenceintensity as standard deviation, σ of air velocity u, divided by local mean velocity, u :

uTI t

σ= (4)

The 19 locations marked in Figure 2 were selected for air velocity measurements.As the experimental room in two of the gloveboxes’ configurations has a ceiling-mountedpassbox, the sampling heights varied depending on location. At locations 7, 8, 9,measurements were made from only the two sampling heights of 60 and 120 cm, whereasfor all sampling locations the sampling heights were approximately 60 (2ft), 120 (4ft) and180 (6ft) cm above the room floor. In the NB room configuration, all three heights weresampled. The sonic anemometer was positioned 50 cm from glovebox faces and theroom walls. Measurements were performed under steady-state conditions, which wasestablished by waiting for at least 5-10 min (one nominal air exchange) after closing andsealing the room door.

Aerosols MeasurementsThe methodology used in the present aerosol study is similar to the one described

in Whicker et al. (1997). Because most releases that occur in LANL workrooms areacute "puff" releases (McAtee 1990), our study focused on short duration releases (60 s).In addition, the data analysis in the present study emphasized the time dependent natureof aerosol dispersion. The time resolution of concentration measurements in this studywas 10 s. This resolution allowed analyses of the time progression of aerosol dispersion.

To simulate an accidental release, polydisperse Dioctyl Sebacate (DOS) oilaerosols were generated using a custom-made orifice nozzle. Operation of the nozzle wasadjusted for releases so aerosol exited the nozzle with low velocity (approximately 1cm s-

1) and quickly accommodated local airflow conditions. The particle size distribution wasapproximately lognormal with the count median diameter of 0.52 µm and geometricstandard deviation of 2.0. From analysis of historical accident data it was concluded thatmost releases took place as a result of some worker action, and not a random event.Therefore the aerosol release nozzle was positioned 120 cm above floor (approximatelychest high, the height of glovebox gloves) to simulate a glovebox-glove-failure typerelease which is the most common cause of airborne releases (Whicker 1993).

An array of sixteen laser particle counters5 (LPCs) was established in the testroom to make aerosol measurements resolved in time and space. Figure 3 shows theaerosol release and LPC locations in the test room. The LPCs were suspended at 120 cmabove room floor. Location and height of LPCs were selected to be close to the breathingzone of a worker at a glovebox workstation. The airflow rates of the LPCs werecontrolled by a critical flow orifice with a sampling rate of about 50 cm3 s-1. All LPCswere coupled to a multiplexer6 and the raw data were recorded every 10 s usingcommercial software7. Raw concentration data were corrected for LPC-specific airflowrates and for particle coincidence counting. A 60-s release at every location was repeatedthree times for quality control, and the results are presented as averages of the threereleases.

For this study, the lag time was used as the metric for comparison among changesin the ventilation rates and room configurations. The lag-time was defined as time fromthe start of the release until the time that an aerosol concentration at sample locationexceeded three standard deviations above background on two consecutive 10-smeasurements.

Data AnalysisThe metrics of lag time, air velocity, airflow direction and turbulence intensity

were stratified by ventilation and room configuration. They were then compared againstone another using non-parametric tests because the measurement distributions were notnormally distributed. The Sign Test was used for the paired comparisons of air velocity,turbulence intensities, and lag times. To look for the effects of room configuration andventilation rates on the variation of lag times across all sampling locations, coefficients ofvariations in the mean lag times were compared using a dependent t-test.

Changes in airflow direction were measured by the angle (in radians) between theflow vectors for each ventilation and room geometry condition. Direction vectors foreach sampling location were paired with the direction vector at the same location butmeasured under either a different ventilation rate (same room configuration) or a differentroom configuration (same ventilation rate). This angle in radians was determined byEquation 5.

5 Models 3755 and 7550, Particle Measuring Systems, 5475 Airport Blvd, Boulder, CO 803016 Model 3701, TSI Inc., 500 Cardigan Rd., St. Paul, MN 55164-03947 Model 390040 Advanced Cleanroom Software, TSI Inc., 500 Cardigan Rd., St. Paul, MN 55164-0394

22

22

22

21

21

21

2121211coszyxzyx

zzyyxx

++×++

++=− θ (5)

Histograms of the changes in airflow direction as ventilation rate changed (holding theroom configuration constant) and as room configuration was altered (holding theventilation rate constant) were made to measure the effects of each of the variables.

CFD AnalysisSignificant progress was made last FY using computer-aided CFD testing of the

effects of alternative ventilation designs on room airflow patterns. Along with ESH-1,and NMT-8, and ESA-DE we identified three alternative designs to be tested against thebaseline design (similar to that in the PF facility). These three alternatives were designedbased on two important criteria. The first was to try and direct airflow in a downwarddirection at the faces of the mock gloveboxes and the second was that the alternativedesign be cost effective and easy to install. The three tested alternative designs includeda cone-shaped diffuser and a ceiling with deflector plates and an air shower design.Figure 4 shows the designs of the supply diffusers. In addition, the impacts of humanson the airflows were studied (Figure 5).

Results

Air velocityFigure 6 shows that the average air velocities for different configurations scaled

similarly up with increased ventilation rate. The increase in mean flow velocitiesbetween low and high ventilation rates were by factors of 2.71, 2.83, and 2.41 for the fullset of gloveboxes (AB), for half gloveboxes removed (HB), and for the empty room(NB), respectively. The minimum and maximum measured air velocity for differentconfigurations varied from 1.6 cm s-1 for NBLV ((Loc. 5 at 60 cm), 1.2 cm s-1 for HBLV(Loc. 6 at 60 cm), and 1.4 cm s-1 for ABLV (Loc. 14 at 60 cm), to 22.9 cm s-1 for NBHV(Loc. 14 at 180 cm), 21.4 cm s-1 for HBHV (Loc. 16 at 120 cm), and 18.5 cm s-1 forABHV (Loc. 16 at 120 cm).

Figure 7 shows the effects of variations in room geometry and ventilation rates onthe direction of airflows as calculated using equation 5. These histograms show thatchanges in direction are mostly less than 90o (1.57 radians) across the variations. Themedian change in angle over the variation in air exchange rate was 0.94 radians with aquartile range of 0.6 to 1.4 radians. The median change in direction for variations acrosschanges in room configuration was 0.92 radians with a quartile range of 0.47 to 1.54radians.

TurbulenceThe capability of turbulence measurements with a sonic anemometer is restricted

by the volume averaging of the sensor due to the 10-cm spacing between transducers.For this reason the sampling frequency used in our study was only 1 Hz, which is belowtypical sampling frequencies used in thermal anemometry. However, the advantages of

obtaining directional information about the airflow may compensate for thesedeficiencies.

The average values of TI were very similar for all configurations and ventilationrates. Because CFD simulations often assume isotropic turbulence (i.e. at any point in theflow the mean-square values of the three fluctuating components are equal

2z

2y

2x σ=σ=σ ), the validity of this assumption for the studied room configuration and

ventilation rate was checked. The results are presented in Table 1. The variances of air-velocity-components averaged for all 19 sonic anemometer locations for a particularroom geometry and ventilation rate are very similar suggesting that the turbulence wasapproximately isotropic for each room and ventilation condition.

AerosolsOne of the primary objectives of the study was to obtain data on aerosol

dispersion, especially in regard to transport time. The metrics used for this purpose werethe lag time and lag time to the maximum concentration defined earlier in section:Aerosol Measurements. The response time is the critical parameter in placement of airmonitors in a work place. Figure 4 shows the decrease in mean lag times with increasingventilation rate, and Figure 8 compares the distributions of lag times categorized by roomand ventilation configuration.

The two-fold increase in ventilation rate resulted in the decrease of the lag time bya factor of 2.0, 1.7, and 1.9 for AB, HB, and NB configuration, respectively. It isinteresting to notice the difference in lag time to the beginning of aerosol cloud to lagtime to maximum aerosol concentration by a factor of about 2.5. This finding couldprovide data for revision of some common assumptions used in e.g., industrial hygienelike instantaneous mixing of particulate air pollutants or the times needed for evacuationof contaminated facility. There was also a strong dependence of average lag time on therelease location. For example, for the ABLV release at Loc III the average lag time was83 s, versus 223 s for release at Loc I.

The influence of ventilation rate on aerosol dispersion (mixing) rate was studiedin more detail by comparing the variation of lag times across all sampling locations foreach release. Figure 9 shows the effects of room configuration and ventilation rate on thecoefficient of variation of mean lag times as measured across all LPCs in the room foreach release location. Statistical comparisons showed that there was a general decreasein the coefficient of variation as glovebox lines were removed. This suggests thatcomplete aerosol mixing throughout the room is more rapid when there were fewerfurnishings in the room. We found no significant differences in the COV when only theventilation rate was varied but the room configuration was the same.

CFD ResultsOf all the supply diffusers analyzed, the air shower with an exhaust located under

the glovebox provided the most protective airflow patterns that would sweep aerosolsdownward and away from the breathing zones. Figures 10 and 11 show the predictedairflow velocities in the horizontal direction at the breathing zone height for the currentdesign and the air shower, respectively. The colors represent a velocity scale withpositive velocities in the upward direction. The velocity vectors for the air shower were

generally downwards at each of the workstations, with the exception of under the trolley.However, the CFD model of each of the designs assumed 7 room air exchanges per hourand this resulted in low air velocities (a few cm/s) with the air shower design. Therefore,it was important to see the effects of human presence at the workstation. Airflow arounda human figure was modeled to both as unheated human (to look at flow blockage only)and as a heated human. Preliminary results suggest that humans create significantalterations in local airflow patterns, which could have significant implications whentrying to estimate worker exposure. However, the effects of a worker’s presence could belocalized and may not significantly affect the general airflow patterns in the room.

DiscussionThe objective of the study was to investigate how the changes in the room

geometry and ventilation rates influence airflow and aerosol dispersion. Changes in thesevariables occur quite often in many research facilities that contain toxic materials.Therefore, studying their effects is important when evaluating the worker protection adistribution of air monitors in a room provides or for accurate interpretation of airsample results under varying conditions.

We found that ventilation rate (for the same room configuration) significantlyaffected lag times and airflow velocities, but not turbulence intensity. As ventilationrates increased the lag times decreased which is likely tied directly to the increase inairflow velocities. The rate that aerosols were transported through the rooms also wasaffected by turbulent eddies. We found that as the airflow velocities increase, thedeviations of the velocities also increased proportionally. This resulted in the relativelyconstant turbulence intensity across all strata of ventilation rate and room configuration.This suggests that the rate of aerosol dispersion, as reflected by the lag time, is effectedby both the airflow velocities in a room, but also by turbulent diffusion rate. Thisconfirms the findings of Siurna and Bragg (1986) who showed that the velocity field andturbulence fields are of fundamental importance in contaminant dispersion by roomventilation. We did find that turbulence intensity appeared to be linearly related toairflow velocity, which may also suggest a non-linear relationship between aerosoldispersion rates and ventilation rate because the dispersion rates are affected by bothairflow velocity and turbulence. Finally, changes in ventilation rate, while affectingairflow velocities, did not seem to completely alter the direction of the airflows. Wefound that over 75% of the changes in direction were less than 1.4 radians (80o ) whenchanges in ventilation alone were considered.

In addition, the results suggested that changes in the room configuration (for thesame ventilation rate) had significant effects on the mean lag times, the COV of thesemean lag times, but generally had little effect on the direction of the airflow vector, meanairflow velocities, or the turbulence intensity. In general, there was a trend for lag time todecrease with removal of the mock glovebox sections. It is suggested that room structurehas a tendency to slow down mixing by creating areas of relatively stagnate air or airpockets. Removal of the furnishings allows the aerosol to mix more rapidly. Changes inroom configuration had no significant effect on airflow velocities, except between HBLVand NBLV experimental setup where the HBLV resulted in higher velocities. It is hardto determine if this is due to experimental uncertainty or perhaps to the presence of the

structure in the room increasing the air exchange rate and consequently the airflowvelocities.

It is also possible that there is an effect not only of adding structure in a room, butalso of placement of the structure relative to the airflow direction and velocity. Buchanan(1995) suggested this effect as they found an increase in mixing with an increase in theairflow disturbance. However, the effects of room furnishings and airflow characteristicson worker exposure are complex. Flynn et al. (1996) found that, under certain airflowconditions, the presence of an object could impede contaminant removal from thebreathing zone of a worker unless the airflow was from the side of an worker and sweptthe airborne material out of the space between the worker and the furnishing.

DeliverablesThe deliverables included evaluations of a number of possible ventilation and

containment configurations that designed to create favorable airflow patterns, on whichrecommendations will be based. Also, valuable information on CFD model validationwas obtained, along with a sensitivity analysis to help determine the important variablesinfluencing the capture efficiency of slot-boxes and local airflow patterns. The largeraudience of safety professionals and facility owners were made aware of our findingsthrough technical presentations and peer-reviewed articles.

Peer-reviewed publicationsRodgers, J.C.; Whicker, J.J.; Voss, J.T. “Comparison of continuous air monitorutilization: a case study,” Radiation Protection Management, May/June:56-64, 1998.

Wasiolek, P.T.; Whicker, J.J.; Gong, H.; Rodgers, J.C. “Room airflow studies usingsonic anemometry,” Indoor Air, Vol. 9: 125-133, 1999.

Wasiolek, P.T.; Whicker, J.J.; Tavani, R. “Influence of room geometry and ventilationrate on aerosol dispersion,” Submitted to Indoor Air, 1999.

Whicker, J.J.; Baker, G.; Wasiolek, P.T. “Quantitative measurements of airflows in aplutonium laboratory,” Submitted to Health Physics, 1999.

Whicker, J.J.; Rodgers, J.C.; Lopez, R.C. “ Assessment of need for transport tubes whencontinuously monitoring for radioactive aerosols,” Health Physics, Vol. 77(3): 322-327,1999.Other PublicationsWhicker, J.J.; Rodgers, J.C.; Wasiolek, P.T. “Implications of room ventilation andcontainment design to minimize worker exposure to plutonium aerosols,” In: TechnologyDevelopment, Evaluation, and Application (TDEA) FY 1998 Progress Report, LA-13579-PR, 1999.

Baker, G. “Air Flow Pattern Studies Using Sonic Anemometry”, Master’s Thesis,University of New Mexico, 1999.

PresentationsKonecni, S.; Parietti, L.M.; Whicker, J.J.; Martin, R.A. “Computation and measurementof turbulent dispersion of toxic aerosols and gases in enclosures,” Los Alamos NationalLaboratory Report LAUR-99-2330, Presented at the Third Biennial Tri-LaboratoryEngineering Conference on Modeling and Simulation, 1999.

Whicker, J.J.; Wasiolek, P.T.; Ammerman, C.; Rodgers, J.C.; Martin, R.; Tavani, R.“Studies on the effects of air distribution on aerosol mixing in rooms,” Los AlamosNational Laboratory Report LAUR-99-803, Presented to the DOE Air Monitor User’sGroup Meeting, Santa Fe, NM, 1999.

Martin, R.; Whicker, J.J. “HVAC Design and Tritium sensor placement evaluationsusing experiments and CFD,” Los Alamos National Laboratory report LAUR-99-5871,invited technical seminar at the Savannah River Site, SC, 1999.

ReferencesBuchanan, C.R., Chung, I.P. and Dunn-Rankin, D. (1995) “A numerical study of indoorcontaminant mixing” Journal of the Institute of Environmental Sciences, 9/10: 15-21.

Cheng, M., Liu, G.R., Lam, K.Y., Cai, W.J. and Lee, E.L. (1999) “Approaches forimproving airflow uniformity in unidirectional flow cleanrooms”, Building andEnvironment 34: 275-284.

Drescher, A.C.; Park, D.Y., Yost, M.G., Gadgil, A.J., Levine, S.P. and Nazaroff, W.W.(1997) “Stationary and time-dependent indoor tracer-gas concentration profiles measuredby OP-FTIR remote sensing and SBFM-computed tomography,” AtmosphericEnvironment, 31(5): 727-740.

Flynn, M.R., Lackey, B.D. and Muthedath, P. (1996) “Experimental and numericalstudies on the impact of work practices used to control exposures occurring in booth-typehoods.” American Industrial Hygiene Association Journal, 57: 469-475.

Hanzawa, H., Melikov, A.K. and Fanger, P.O. (1987) “Airflow characteristics in theoccupied zone of ventilated spaces”, ASHRAE Transactions 93(1): 524-539.

Nicas, M. (1996) “Estimating exposure intensity in an imperfectly mixed room”,American Industrial Hygiene Association Journal 57: 542-550.

McAtee, J.L. (1990) “Interrelationship among personnel dosimetry and other workplacemonitoring methods”, Report LA-UR-90-0664, Los Alamos National Laboratory, LosAlamos, NM.

Nielsen, P.V., (1998) “The selection of turbulence models for prediction of roomairflow,” ASHRAE Transactions Symposia, SF-98-10-1, pp. 1119-1127.

Siurna, D.L., and Bragg. G.M. (1986) “Stochastic modelling of room air diffusion.Ventilation’85, Elsevier Science Publishers.

Stull, R.B. (1988) An Introduction to Boundary Layer Meteorology, Dordrecht, TheNetherlands, Kluwer Academic Publishing.

Vogt, R. (1997) “Intercomparison of ultrasonic anemometers”, Proc. 12th Symposium onBoundary Layers and Turbulence, Vancouver, BC, Canada, July 28-August 1, 1997

Wasiolek, P.T., Whicker, J.J. Gong, H. and Rodgers J.C. (1999) “Room airflow studiesusing sonic anemometry”, Indoor Air 9: 125-133.

Whicker J.J. (1993) “Continuous air monitor correlation to fixed air sample data at LosAlamos National Laboratory”. Proc. DOE 1993 Radiation Protection Workshop, CONF-9304128, Las Vegas, NV April 13-15, 1993.

Whicker, J.J., Rodgers, J.C. Fairchild, C.I. Scripsick, R.C. and Lopez R.C. (1997)“Evaluation of continuous air monitor placement in a plutonium facility”, Health Physics,2(5): 734-743.

Yost, M.G, and Spear R.C. (1992) “Measuring indoor airflow patterns by using a sonicvector anemometer”, American Industrial Hygienist Association Journal, 53(11): 677-680.

Table 1. Mean square values of the fluctuating velocity components for different roomsetup and ventilation rate.

2xσ 2

yσ 2zσ

ABLV 2.79 3.16 2.61

ABHV 17.63 16.47 16.86

HBLV 2.92 3.04 3.35

HBHV 18.74 19.07 18.24

NBLV 2.95 3.02 2.94

NBHV 18.57 17.37 16.87

Y

X

X

Z

A-A

A-A

480 cm

240

cm61

0 cm

90 cm

120

cm

120

cm

60 c

m

100 cm

Glovebox Glovebox

Passbox

Glovebox

Glovebox

Passbox

Blo

wer

Y

X

X

Z

A-A

A-A

480 cm

240

cm61

0 cm

90 cm

120

cm

120

cm

60 c

m

Glovebox Glovebox

Passbox

Glovebox

Glovebox

Passbox

Blo

wer

Y

X

X

Z

A-A

A-A

480 cm

240

cm61

0 cm

Blo

wer

a) b) c)

Figure 1.

Figure 1. Schematic Diagram of the test-room facility with three different configurationsof simulated gloveboxes:

(a) full set of gloveboxes (FB)

(b) half of gloveboxes removed (HB)(c) no gloveboxes or trolley (NB)

60 cm

120 cm

180 cm

240 cm

300cm

360cm

420cm

480cm

540 cm

60 cm 120 cm 180 cm 240 cm 300 cm 360 cm 420 cm

Y

X

1

9

2

1912111018

45

7 8

6 3

1613141517

60 cm

60 cm

120 cm 180 cm 240 cm 300 cm 360 cm 420 cm

120 cm

180 cm

X

Z

A-A

A-A

Sonic Anemometer Location

Figure 2. Locations of sonic anemometer measurements in the experimental room.

60 cm

120 cm

180 cm

240 cm

300cm

360cm

420cm

480cm

540 cm

60 cm 120 cm 180 cm 240 cm 300 cm 360 cm 420 cm

Y

X

I

II

IVV

VI III

60 cm

60 cm

120 cm 180 cm 240 cm 300 cm 360 cm 420 cm

120 cm

180 cm

X

Z

A-A

A-A

1 2 3 4

5 6 7 8

109 11 12

13 14 15 16

LPC LocationAerosol Release Location

Figure 3. Locations of aerosol releases (Roman numerals) and laser particle counters(LPCs) in the experimental room.

Figure 4. Various supply diffuser designs that were tested for downward airflow in thebreathing zone using CFD analysis. Schematic (a) is the current diffuser design, (b) is acone shaped diffuser, and (c) is the air shower design.

Supply air and inlet

(a)

Supply air and inlet

(b)

Supply air and inlet

(c)Glovebox

Figure 5. Glovebox Geometry with Simulated Humans

U T (m/s) STD U T (m/s)%TI T LAGTIME (s)

Figure 6. Plot of UT, the standard deviation of UT, TI T, and the

lag time as affected by ventilation rate and room configuration.

ACH Low

Val

ues

1

10

100

full half emptyACH High

full half empty

(a)

Radians

Num

ber o

f obs

erva

tions

0

6

12

18

24

30

36

42

48

54

60

66

72

78

84

(0-0.5) (0.5,1.0) (1.0-1.5) (1.5-2.0) (2.0-2.5) (2.5,3.0) > 3.0

(b)

Radians

Num

ber o

f obs

erva

tions

0

4

8

12

16

20

24

28

32

36

40

44

48

52

(0-0.5) (0.5-1.0) (1.0-1.5) (1.5-2.0) (2.0-2.5) (2.5-3.0) > 3

Figure 7. Changes in airflow direction with changes in: (a) glovbox configuration, b) ventilation

Min-Max25%-75%Median value

Figure 8. Box & whisker plot of lag times under various room and ventilation conditions.

Room and ventilation conditions

Lag

time

(s)

-50

50

150

250

350

450

ABLV ABHV HBLV HBHV NBLV NBHV

Figure 9. Box & whisker plot of the coefficient of variation among lag times categorized by room and ventilation conditions.

Room and ventilation condition

Coe

ficie

nt o

f Var

iatio

n of

Lag

Tim

es

0.24

0.30

0.36

0.42

0.48

0.54

0.60

ABLV ABHV HBLV HBHV NBLV NBHV

±1.96*Std. Err.±1.00*Std. Err.Mean

Figure 10. CFD result for flat plate diffuser (baseline PF-4 type)

Figure 11. CFD results for air shower diffuser and under glovebox exhausts.