The 2012 World Congress on Advances in Civil, Environmental, and Materials Research (ACEM’ 12)Seoul, Korea, August 26-30, 2012

Wind Effect on Spread of Fire and Smoke

N. Cai1) and W.K. Chow2)

1), 2) Research Centre for Fire Engineering, Department of Building Services

Engineering, The Hong Kong Polytechnic University, Hong Kong, China 2) beelize@polyu.edu.hk

ABSTRACT

After a fire breaks out, smoke will spread radially from the central axis of the plume to higher positions. Cool air will be entrained toward the burning fuel at lower levels of the building. The pressure in the fire plume would be reduced, acting as a pump to entrain larger amount of air. Under wind action, more air will be entrained at the lower level to supply oxygen to burn more fuel. Lateral spread of smoke will then be accelerated. Therefore, fire and smoke would not spread only in the windward direction.

Numerical study of wind effects on the characteristics of fire plume in free space was carried out by Computational Fluid Dynamics (CFD). The Fire Dynamics Simulator (FDS) version 5.5.3 was used as the CFD simulation tool. The geometric properties of flames, the effects of lateral air entrainment on the fire plume, and smoke movement induced by a fire were studied. In addition to the significant flame and smoke spread in the leeward direction, CFD predicted results confirmed that lateral spread of flame and smoke were also accelerated along with an increase of wind velocity in the cross-wind direction. 1. INTRODUCTION

After a flashover room fire starts in a tall building, smoke will move under several factors (McGuire et al.1970). Wind effect is one of the important factors that affect fire behaviour. Smoke will spread radially from the central axis of the plume to higher positions. Cool air will be entrained toward the burning fuel at the lower levels of the building. The pressure in the fire plume would be reduced, acting as a pump to entrain higher amount of air. Under wind action, more air will be entrained at the lower level and give rise to a bigger fire. Among all fire safety issues of high-rise buildings, the safety of evacuation has been identified (Chow 2004) as a key concern. Therefore, it is important to understand wind effects on plume and smoke spread, which is essential to predict the initiation, development, and the spread of building fires.

Investigations of the smoke movement in a fire need to address the

1) PhD Student 2) Chair Professor and Head of Department

fundamental characteristics of fire plumes. Albini (1981) developed a one-dimensional model to simulate wind-blown flames from line fires in which buoyancy is the principal source of vertical momentum. Numerical examples were presented for flames at uniform wind speed. Approximate expressions were found for flame height, length and tilt angle. The thermal plumes arising from large pool fires were simulated by Nam and Bill (1993), using modified standard k-ε turbulence model. Results showed that predicted results by this modified model agreed much better with the experimental results of buoyant thermal plumes. Using a commercial code FLOW3D, Sinai and Owens (1995) modelled a kerosene pool fire subjected to cross-wind with emphasis on flame geometry and the significant factors in the formation of plume shape. It was found that flame shapes were in accordance with experimental observations. Grove and Quintiere (1998) carried out theoretical analysis on the behavior of buoyant diffusion flames from axisymmetric, line and rectangular fire sources in the absence of wind. Snegriev (2004) used a statistical method which incorporated CFD modeling and simulated the interactions between a pool fire and a crosswind. The results showed that the burning rate increases with wind. Chow and Li (2007) simulated fire-induced thermal plumes by four different k-ε turbulence models. Experimental data on pool fires and heptane spray fires reported in the literature are to be compared with numerical results.

Although there have been some theoretical and numerical studies on wind effect on flames, very few studies focus on plume geometry and lateral smoke movement affected by wind. In this study, the main objective is to assess the plume geometry and lateral spread of smoke affected by wind. Numerical study of wind effects on the characteristics of fire plume in free space will be carried out by Computational Fluid Dynamics (CFD). The latest version of CFD model Fire Dynamics Simulator (FDS) version 5.5.3 (McGrattan et al. 2009) was used to simulate the geometric properties of flames, the effects of lateral air entrainment on the fire plume, and smoke movement induced by a fire under different wind speeds. 2. NUMERICAL EXPERIMENT

The latest version 5.5.3 of the FDS was selected as the CFD simulator. A three-dimensional Cartesian coordinate system was used, and Fig. 1(a) shows the length along the x-direction, width along the y-direction, and height along the z-direction. The computational domain was of 12 m length, 12 m width and 12 m height. A pool fire of common design fire size, 5 WM, was assumed at the center of the computational domain. The pool fire was simulated by a polygon with area equal to the circular pan of diameter of 0.2 m. The initial air temperature was 20 oC.

Free boundary conditions were imposed on the outside between the computational domain and the external environment. Fluid can enter or leave the computational domain freely. Pressure at the boundary was taken as the same as the ambient pressure.

According to the LES methodology, the transient signatures comprise of larger eddies and smaller unresolvable eddies. Large eddies are resolvable by the calculation procedures. Smaller eddies are modeled by a time averaged component and a fluctuating perturbation about that average (Cox 2004).

The fineness of the numerical grid determines the size of resolvable eddies and those are not in the LES model. The process of refining the grid system is referred as a grid/mesh sensitivity study.

(a) Schematic diagram

(b) Grid system G1: 1,000,000 cells (c) Grid system G2: 1,728,000 cells (d) Grid system G3: 3,375,000 cells

Fig. 1. The geometry of the numerical simulation mode

For simulations involving buoyant plumes, the non-dimensional expression D*/δx can be used as a parameter measuring the resolving rate of the flow field, where D* is a characteristic fire diameter (McGrattan et al. 2009):

52

*

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛=

∞∞

•

gTCQDpρ

(1)

and δx is the nominal size of a mesh cell. The quantity D*/δx can be assumed to be the number of computational cells spanning the characteristic diameter of the fire. A refined grid system can improve the accuracy of LES results.

It is suggested by McGrattan et al. (1998) that the value of D*/δX should be larger than 10 to guarantee reliable operation of FDS. This value has been confirmed by Merci and Van Maele’s study (2008), and it is be acceptable for FDS simulation. Other researchers, such as Zou and Chow (2005), also obtained reasonable FDS predictions of temperature and radiation data using D*/δX of ≈14. The results of

z

y

x

Wind Direction

FireDy

Dx

z

x

y

z

study by Hietaniemi et al. (2004) on pool fire showed that at least 20 cells should be placed within the diameter of the pool to obtain reliable experiment data.

For the optimum resolution for flame height simulation, Ma and Quintiere (2003) gave an even stricter criterion. The non-dimensional expression R* related to the grid size of ∆x , ∆y and ∆z with the characteristic fire diameter D* is defined as:

** ),,max(

DzyxR ∆∆∆

=

(2)

Using this non-dimensional expression, R* was suggested to be around 0.05

for optimum resolution of a pool fire simulation. To investigate the effect of grid size on the predicted flow field, four different

grid systems G1, G2, G3 and G4 of uniform distribution were tested under a 5 MW fire. The grid systems are shown in Fig. 1(b) to 1(d). The value of R* varied from 0.04 to 0.07, D*/δvaried from 15 to 22. • Grid system G1 with R* of 0.04 and D*/δof 15: 1,000,000 cells with grid size of

0.12 m • Grid system G2 with R* of 0.05 and D*/δof 18: 1,728,000 cells with grid size of 0.1 m

• Grid system G3 with R* of 0.07 and D*/δof 22: 3,375,000 cells with grid size of 0.08 m

3

3

3

(a) System G1 of 1,000,000 cells (b) System G2 of 1,728,000 cells (c) System G3 of 3,375,000 cells

Fig. 2. Velocity vectors predicted for different grid system without wind

Fig. 2 shows the velocity vectors predicted by these three different grid systems under a 5 MW fire. Fig. 3 shows pictures on massless particles distribution to trace smoke motion at the plane of Y = 6 m. It is observed that the finer grid system G2 and G3 can give reasonable good results on entrainment of plume and the vortex shedding from the base of fire to the upwards. Taking the accuracy and cost of CPU time into account, the grid system G2 with 1,728,000 cells was used for the simulations under different wind conditions in this study.

(a) System G1 of 1,000,000 cells (b) System G2 of 1,728,000 cells (c) System G3 of 3,375,000 cells

Fig. 3. Massless particles predicted for different grid systems without wind 3. WIND EFFECT

Wind boundary was imposed on the side facing wall A of the building. Free boundary conditions were applied on the remaining parts between the computational domain and the external environment. A typical atmospheric wind profile can be described as:

pzzuu )/( 00= (3) u0 is the velocity at the reference height z0, z is the ground level, p is the atmospheric profile exponent. In this case, the default value of the reference height z0 and the atmospheric profile exponent p, 10 m and 0.3 are taken.

Using the wind velocity u0 as a characteristic velocity, Froude number (Fr) can be defined in terms of the fire width d and the gravitational acceleration g as:

gduFr /20= (4)

Five wind velocities have been tested are u0 = 0.5, 1.0, 1.5, 2.0 and 2.5 m/s.

The corresponding values of the Froude number are Fr = 0.127, 0.510, 1.148, 2.041 and 3.189. 4. RESULTS

In addition to the no wind condition, six simulations were conducted by FDS at varied wind speeds 0.5, 1.0, 1.5, 2.0 and 2.5 m/s. All numerical simulations were generated under the same heat release rate 5 MW.

Smoke and particles distribution in leeward direction (x direction) are insensitive to wind velocity lower than 1.0 m/s, however, the distribution increases significantly when the wind velocity increases 0 to 1.0 m/s, as shown in Fig. 4. As in Fig. 5, in cross-wind direction (y direction), the distribution of smoke and particles indicates that the lateral spread of smoke increases with wind velocity. This relation may be prompted by the rise of turbulence level resulted from high wind velocity.

(a) u0 = 0 m/s (b) u0 = 0.5 m/s (c) u0 =1. 0 m/s

(d) u0 = 1.5 m/s (e) u0 = 2.0 m/s (f) u0 = 2.5 m/s

Fig. 4. Smoke and particles distribution in leeward direction Table 1 The distance in x direction and y direction covered by the flame tip ( Dx / Dy) Z (m) u0 (m/s) Dx / Dy (m)

2 4 6 8 10

0 Dx 1 1.3 2.4 2.2 1.3 Dy 0.6 1.1 2.3 1.8 1.9

0.5 Dx 1.3 1.1 2.1 2.1 2.4 Dy 1.1 1.3 1.7 2.4 1.5

1 Dx 1 1.5 2.9 1.8 2.6 Dy 0.9 2.1 2 2.9 1.8

1.5 Dx 1.5 0.9 1.6 2.1 3.4 Dy 1.3 1.8 1.8 2.9 2.9

2 Dx 1.5 2.2 3.3 N/A N/A Dy 1.3 2.8 1.7 N/A N/A

2.5 Dx 0.9 2.2 3 N/A N/A Dy 1.2 2.9 2.4 N/A N/A

z

y

x

(a) u0 = 0 m/s (b) u0 = 0.5 m/s (c) u0 =1. 0 m/s

(d) u0 = 1.5 m/s (e) u0 = 2.0 m/s (f) u0 = 2.5 m/s

Fig. 5. Smoke and particles distribution in cross-wind direction

Albini (1981) gave the definition of the flame tip as the height at which the mean temperature descended below 500 K. This definition was adopted here to define the average flame tip. Figs. 6 to 10 show the distribution of flame tip when the gas temperature ranges from 400 K to 500 K at the planes of z = 2.0 m, 4.0 m, 6.0 m, 8.0 m and 10.0 m. The geometry of the flame tip under windy conditions is totally different from that when there is no wind. However, for the lightest wind considered (u0 = 0.5 m/s, Fr = 0.127), the distance (Dx and Dy) in x and y direction covered by the flame tip (as shown in Tab. 1, Fig.1 and Figs. 6 to 10) are very similar to the results obtained from the case without wind. With increasing wind velocity, the predicted results show that the positions of the flame tip are strongly influenced in both windward and cross-wind directions. Significant spread in leeward direction was observed. In all planes at different height z, the higher the wind velocity is, the further the flame tip can reach, and the larger the range the flame tip can cover in the x direction. The same pattern can be found in the y direction for the range the flame tip covered. No points can reach the temperature of 400 K to 500 K above the planes of 8.0 m when the wind velocity increases to 2 m/s, indicating the wind effects dominate and reduce the vertical development of the flame. These can also be observed in Fig. 4. As the wind velocity increases, the plumes bent over further by the approaching wind.

z

y x

5.5 6.0 6.5 7.0 7.5 8.05.0

5.5

6.0

6.5

7.0

Y

X

5.5 6.0 6.5 7.0 7.5 8.05.0

5.5

6.0

6.5

7.0

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X

5.5 6.0 6.5 7.0 7.5 8.05.0

5.5

6.0

6.5

7.0

Y

X

(a) Without wind (b) Wind speed u0 = 0.5 m/s (c) Wind speed u0 = 1.0 m/s

5.5 6.0 6.5 7.0 7.5 8.0

5.0

5.5

6.0

6.5

7.0

Y

X

5.5 6.0 6.5 7.0 7.5 8.05.0

5.5

6.0

6.5

7.0

Y

X

5.5 6.0 6.5 7.0 7.5 8.0

5.0

5.5

6.0

6.5

7.0

Y

X

(d) Wind speed u0 = 1.5 m/s (e) Wind speed u0 = 2.0 m/s (f) Wind speed u0 = 2.5 m/s

Fig. 6. Distribution of the flame tip between 400 K and 500 K of the gas temperature in the horizontal plane z = 2.0 m

5 6 7 8 9

5

6

7

Y

X

5 6 7 8 9

5

6

7

Y

X

5 6 7 8 9

5

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(a) Without wind (b) Wind speed u0 = 0.5 m/s (c) Wind speed u0 = 1.0 m/s

5 6 7 8 9

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7

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X

5 6 7 8 9

5

6

7

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5 6 7 8 9

5

6

7

Y

X

(d) Wind speed u0 = 1.5 m/s (e) Wind speed u0 = 2.0 m/s (f) Wind speed u0 = 2.5 m/s

Fig. 7. Distribution of the flame tip between 400 K and 500 K of the gas temperature in the horizontal plane z = 2.0 m

DyDx

5 6 7 8 9 10

5

6

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8

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X

5 6 7 8 9 10

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8

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5 6 7 8 9 10

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(a) Without wind (b) Wind speed u0 = 0.5 m/s (c) Wind speed u0 = 1.0 m/s

5 6 7 8 9 10

5

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X

5 6 7 8 9 10

5

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8

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5 6 7 8 9 10

5

6

7

8

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X

(d) Wind speed u0 = 1.5 m/s (e) Wind speed u0 = 2.0 m/s (f) Wind speed u0 = 2.5 m/s

Fig. 8. Distribution of the flame tip between 400 K and 500 K of the gas temperature in the horizontal plane z = 2.0 m

5. CONCLUSIONS

Numerical studies on flame geometry and smoke movement induced by a fire under windy conditions were carried out by FDS. In addition to the significant flame and smoke spread in the leeward direction, predicted results showed that lateral spread of flame and smoke are also directly proportional to wind velocity in the cross-wind direction. These may be due to the rise of turbulence level resulted from high wind velocity.

As the wind velocity increases, the plumes bent over further by the approaching wind. This is different from the case when there is no wind. Smoke will spread radially from the central axis of the plume to higher positions. Excessive wind-driven makeup air would spread smoke at the lower level under higher wind speed.

The above points should be taken into account in the future building fire safety design. Smoke will spread to buildings at the lateral side. This is particularly important in very tall buildings in which high stack pressures were also found (Jo et al. 2007) on to high wind speed at the upper levels. Smoke spread due to wind, stack effect and thermal buoyancy caused by a fire should be studied carefully. ACKNOWLEDGEMENT

The work described in this paper was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China for the project “Appropriate Safety for Lift shafts and Adjacent Lobbies of Evacuation Elevator Systems for Supertall Buildings under Big Fires” (PolyU 5148/08E) with account number B-Q11T.

5 6 7 8

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5 6 7 8

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(a) Without wind (b) Wind speed u0 = 0.5 m/s

5 6 7 8

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8

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X

5 6 7 8

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6

7

8

Y

X

(c) Wind speed u0 = 1.0 m/s (d) Wind speed u0 = 1.5 m/s

Fig. 9. Distribution of the flame tip between 400 K and 500 K of the gas temperature in the horizontal plane z = 8.0 m

5 6 7 8 9

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5 6 7 8 9

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(a) Without wind (b) Wind speed u0 = 0.5 m/s

5 6 7 8 9

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5 6 7 8 9

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X

(c) Wind speed u0 = 1.0 m/s (d) Wind speed u0 = 1.5 m/s Fig. 10. Distribution of the flame tip between 400 K and 500 K of the gas temperature

in the horizontal plane z = 10.0 m

REFERENCES Albini F.A., (1981). “A model for the wind-blown flame from a line fire,” Combust. Flame, Vol. 43, 155-174. Chow W.K., (2004-2005). “Evacuation in a supertall residential complex,” J. Appl. Fire Sci., Vol. 13, 291-300. Chow W.K. and Li J., (2007). “Numerical simulations on thermal plumes with k–ε types of turbulence models,” Build. Environ., Vol. 42(8), 2819-2828. Cox G., (2004 ). “Fire Modelling,” Building Research Establishment Digests DG367, 2nd Edition Edition, Building Research Establishment, Watford, UK. Grove B.S., Quintiere J.G., (1998). “Unified Analysis for Fire Plumes” Proceedings of the 27th Symposium (Int.) on Combustion, the Combustion Institute, Pittsburgh. Hietaniemi J., Hostikka S. and Vaari J., (2004) “FDS simulation of fire spread comparison of model results with experimental data,” VTT Working Papers 4, VTT Technical Research Center of Finland. Jo J., Lim J., Song S., Yeo M. and Kim K., (2007). “Characteristics of pressure distribution and solution to the problems caused by stack effect in high-rise residential buildings,” Build. Environ., Vol. 42(1), 263-277. Ma T.G. and Quintiere J.G., (2003). “Numerical simulation of axi-symmetric fire plumes: accuracy and limitations,” Fire Saf. J., Vol. 38(9), 467-492. McGrattan K.B., Klein B., Hostikka S. and Floyd J. E., (2009). “Fire Dynamics Simulator (Version 5), User's Guide,” NIST Special Publication 1019-5, National Institute of Standards and Technology, Gaithersburg, MD, USA. McGrattan K.B., Baum H.R. and Rehm R.G., (1998). “Large eddy simulations of smoke movement,” Fire Saf. J., Vol. 30(3), 161-178. McGuire J.H., Tamura G.T. and Wilson A.G. (1970). “Factors in Controlling Smoke in High Buildings,” Proceedings of the Symposium on Fire Hazards in Buildings, San Francisco. Merci B. and Van Maele K., (2008) “Numerical simulations of full-scale enclosure fires in a small compartment with natural roof ventilation,” Fire Saf. J., Vol. 43(10), 495-511. Nam S. and Bill R. G. Jr., (1993 ). “Numerical simulation of thermal plumes,” Fire Saf. J., Vol. 21, 231-256. Sinai Y.L. and Owens M.P., (1995). “Validation of CFD modelling of unconfined pool fires with cross-wind: Flame geometry,” Fire Saf. J., Vol. 24, 1-34. Snegirev A.Y., (2004). “Statistical modeling of thermal radiation transfer in buoyant turbulent diffusion flames,” Combust. Flame, Vol. 136(1), 51-71. Zou G.W. and Chow W.K., (2005). “Evaluation of the field model, fire dynamics simulator, for a specific experimental scenario,” J. Fire Prot. Eng., Vol. 15, 77-92.