ANALYSIS OF PERFORMANCE-BASED SMOKE MANAGEMENT SYSTEM DESIGN IN A SHOPPING MALL

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1 , Volume 1, Number 4, p , 2 ANALYSIS OF PERFORMANCE-BASED SMOKE MANAGEMENT SYSTEM DESIGN IN A SHOPPING MALL K.H. Yang and J.N. Lee Mechanical Engineering Department, National Sun Yat-Sen Uniersity, Kaohsiung, Taiwan 8424, R.O.C. (Receied 2 September 2; Accepted 16 Noember 2) ABSTRACT In Taiwan, the fire code is still prescriptie in nature which fails to proide effectie design guide for buildings with large spaces and atria. In this paper, the NFPA 92B has been adapted to deelop a design procedure of smoke management system in a shopping mall atrium using performance-based fire safety design method. The objecties of this design procedure are assurance of safe eacuation and preention of fire spread to adjacent space. The authors implemented this design procedure to the fire safety system of a shopping mall in Taipei, and obtained approal from authorities haing jurisdiction as a successful performance-based design. This paper demonstrated the complete design procedure as an example to fire safety engineers. 1. INTRODUCTION In 1996, the new prescriptie fire code was implemented in Taiwan [1]. On item 189, No. 7, it stated that the smoke exhaust rate should not be less than 12 m 3 min -1. And in zoned smoke control designs, each zone should be equipped with mechanical smoke exhaust rate for more than 1 m 3 min -1 per floor area. The minimum legitimate smoke exhaust rate, which directly related to building floor area, is apparently misleading, especially when large spaces or an atrium is encountered. Table 1 shows a calculation comparison of the smoke generation rate between that of Taiwan fire code and the NFPA 92B [2]. The deiation could be up to 6 times. The deiation lies mainly in that the prescriptie code ignored the large air entrainment olume of an atrium when a fire occurred, although it still seres as a feasible guide for ordinary office buildings. Table 1: Comparison of the smoke generation rate between Taiwan fire code and the NFPA 92B for a 5 m 2 room (5 MW fire) Design smoke clear height NFPA 92B Taiwan Fire Code 1.5 m 5.35 m 3 s m 3 s m 7.13 m 3 s m 3 s m 8.92 m 3 s m 3 s m m 3 s m 3 s m 47.8 m 3 s m 3 s -1 In performance-based fire safety design, the procedure includes the following sub-systems as shown in Fig. 1. Design Fire Size Analysis Fire Detection and Suppression System Design Smoke Management System Design Eacuation Analysis, and Quantitatie Risk Assessment These sub-systems were discussed in detail as follows. 2. PERFORMANCE - BASED FIRE SAFETY DESIGN METHOD 2.1 Design Fire Size Design fire size analysis is the most important step in fire hazard assessment, which directly related to the ealuation of smoke descending rate and adequate sizing of smoke management system. Generally, the design fire size falls into three categories: a. Steady fire assumption A fixed heat release rate was assumed in this case, for example, 5 MW in an office building [3], and 2 MW to 3 MW in an underground railway station, or subway systems [4], etc. b. Unsteady fire assumptions To simulate the fire growth period until it reaches the steady state, normally an unsteady fire is assumed. The most widely applied unsteady fire assumption is the t-squared fire, the heat release rate is directly proportional to the square of time elapsed, or in equation form: Q 2 = a( t t ) (1) 181

2 Start Building Geometry Design Fire Size Fire Detection & Suppression System Design Humane Behaior Eacuation Smoke Management System Design Quatitatie Risk Asessment Mechanical Ventilation Natural Ventilation Hybrid Ventilation Modify the number or Width of Exits Modify Smoke Extraction Rate No ASET>RSET No Yes To compile the integrated emergency procedure End Fig. 1: Flow chart of performance-based fire safety design method Q = heat release rate or the fire size in kw t = effectie ignition time t = actual time elapsed a = fire growth rate In NFPA 92B, four different types of t 2 -fire were assumed as shown in Fig. 2. The designer has to choose one which fits well with the project under inestigation. Sometimes a full-scale test should be arranged to alidate the assumption, such as a wet-bench fire of a semi-conductor clear room, or an actual carriage fire set inside a ehicle tunnel. c. Measured fire growth A measured fire growth cure is utilizing test data from Cone-Calorimetry, a bench-scale test or a full-scale test, and cure-fitted to represent the actual heat release rate [5]. The cures obtained normally presumes more accurate, but sometimes restricted by the test assumptions. The design engineer normally picks one of these methods as a start to size the fire protection system. 2.2 Fire Detection and Suppression System Design Normally, the smoke detectors and sprinklers were installed on the ceiling of a building. In an atrium, the fire/smoke detection system design needs extra considerations. The atrium not only proides large space for smoke storage in case of a fire, but could easily become pre-stratified with a layer of hot air in the summer, especially in a sky-lighted atrium. The smoke buoyancy was counter-balanced by the hot air causing the fire/smoke detectors unable to be actuated. In NFPA 92B, the formation of smoke stratification can be calculated from: z ( T ) 3/8 1/4 m = 5.54Qc / dz (2) Z m = maximum height of smoke rise aboe fire surface (m) Q c = conectie portion of the heat release rate (kw) T / dz = rate of change of ambient temperature with respect to height (C/m) On the other hand, when ordinary sprinkler system was actiated in an atrium, the water droplet could 182

3 Fig. 2: Relation of t-squared fires to some fire tests be eaporated so quickly and becoming water mist before hitting the fire source. An actual fire occurred seeral years ago in CKS airport terminal I showed that the water sprayed in this case is more like a cloud clustered in the middle of the atrium and became inert. NFPA 92B suggested that the sprinkler system should be installed with 2.4 to 7.6 m (8 to 25 ft) height normally for escalator or cabin protection in an atrium. For the large space, long-range water cannon with infra-red detection is sometimes utilized. 2.3 Smoke Management System Design Smoke management can be achieed by designing mechanical and natural enting systems. But before that, the natural smoke filling process should be ealuated. a. Smoke filling process ealuation In order to ealuate the aailable safety egress time (ASET), the smoke filling of the atrium and the smoke descending rate can be calculated by: d A ( ρ( H y) ) dt = m p (3) During the natural smoke filling process, the smoke descending rate is closely related to the fire plume air entrainment mass flow rate, the most commonly applied prediction models were listed in Table 2 [6-9]. Fig. 3 shows the fire plume air entrainment mass flow rate under arious heights of a 5 MW fire. This figure depicts that the smoke mass flow rate calculated by the CFAST plume model is obiously too high, could be 92.5% higher than that calculated by the NFPA 92B plume model at the atrium height of 3 m. In Fig. 4, the BRI (Building Research Institute, Japan) [1] and NRCC (National Research Council of Canada) [11] test data were plotted to compare with the simulation result. It indicated the NFPA 92B has the best correlation with experimental data, and is adapted as our calculation model afterwards in the design example. When the required safe egress time (RSET) is larger than the ASET mentioned aboe, smoke management system should be installed as a remedial measure. b. Mechanical smoke exhaust system design The design step can be shown as: 1. Design the allowable smoke clear height. 2. Use NFPA 92B plume model or other models to calculate the smoke (air) entrainment mass flow rate ( m p ). 3. Size the smoke exhaust system capacity mext m p. The smoke descending rate of an atrium can thus be calculated by: d A ( ρ( H y) ) dt = m p mext (4) 183

4 Table 2: Formula of fire plume air entrainment mass flow rate Heskstad (NFPA 92B) McCaffrey (CFAST) Thomas et al. Zukoski et al. 5 / 3 Flame region: m p =.32Qc ( z z ) Plume region: m p.71q 1/ ( z z ) 5 / 1+.26Q 2 / ( z z ) Virtual origin: Flame Height: 3 [ ] 5 / c = c 2 / 5 z = 1.2D +.83Q L = m p 2 / 5.166Qc.566 Flame region: z z =.11. <. 8 2 / 5 2 / Q 5 Q Q m p Intermittent region: z z =.26.8 <. 2 2 / 5 2 / Q 5 Q Q Plume region: m p Q z z = / 5 Q Q p = p = / p 1 / 2 1.5A f 2 / 5 Flame region: ( ) 1/ 2 3 / 2 ( ) m.96ρ gρ fl / ρ P z z 3 5 / 3 Plume region: m.153( gρ Q c T ) 1 / ( z z ) Virtual origin: z = 1/ 3 = p Plume region: m p.21( gρ ) 2 / c T Q 1/ 3 ( z z ) 5 / 3 Virtual origin: With floor: z =.5D +. 33L Without floor: z =.8D +. 33L Flame Height : * D * 2 / 3 1. : L / D 3.3QD Q < = * D * 2 / 5 1. : L / D 3.3QD Q = * 2 2 Q = Q /[ ρ c T ( gd) ] 1 / D D p entrainment Entrainment mass Mass flow Flow rate (kg/s) Rate (kgs -1 ) 7 Zukoski Plume model 65 NFPA 92B Plume model 6 McCaffrey Plume model Clear Height (m) Fig. 3: Fire plume air entrainment mass flow rate under arious heights of a 5 MW fire 184

5 Smoke Clear Height (m) NFPA Plume model Zukoski Plume model NRCC data BRI data Time (sec) Fig. 4: Comparison of the predictions of smoke-layer position with the experimental data Smoke Clear Height(m) 3 Visual in BRI test Judged by Temperature Measurements in BRI test NFPA 92B Plume Model in BRI Test 25 Judged by Temperature Measurements in this study Visual in this study Video in this study 2 NFPA 92B Plume Model in this study Time(sec) Fig. 5: Comparison of the predictions of smoke-layer position with experimental data for the case with mechanical entilation of 6 m 3 s -1 Fig. 5 shows the alidation of this model by a full-scale experiment performed by BRI (Building Research Institute, Japan) [1] with mechanical smoke exhaust rate of 6. m 3 s -1. At the early 8 s, the predicted smoke clear height is lower than that measured since the time lag is not counted effectiely. Otherwise, the correlation is good. The authors conducted a full-scale experiment of an atrium fire in another research project. The actual smoke layer positions were recorded isually with a ideo-camera and further identified with thermocouple measurements. The correlation is quite satisfactory between the simulation and experimental work, and the calculation model has thus been adapted for our design projects afterwards. c. Natural entilation system design The smoke management system can be optimized, if natural and mechanical smoke exhaust were combined into a hybrid system, exhaust fans can be downsized significantly. The natural smoke ent introduces a turbulent air moing process due to high buoyancy and thus heaily depends on smoke layer temperature and 185

6 thickness. In our designs, natural smoke exhaust rate was calculated using Morgan s experimental equation [12], or: A C m n = ρ T 2 s ( A C / A C ) + i 2gD T T B s i 2 T T s 1/ 2 (5) A = measured throat area of entilators (m 2 ) A i = total area of all inlets (m 2 ) C i = entry coefficient for all inlets (typically about.6) C = coefficient of discharge (usually between.5 and.7) D B = depth of smoke beneath entilator (m) g = acceleration of graity (ms -2 ) m n = mass flow rate of smoke to be extracted (kgs -1 ) T s = absolute temperature of smoke layer (K) T = absolute temperature of ambient air (K) T s = temperature rise of smoke layer aboe ambient (C) ρ = density (ms -2 ) The calculation procedure can be summarized as in Fig. 6. Start Assume allowable smoke clear height Calculate smoke generation rate using designed fire size Calculate smoke layer temperature by Q Ts = T + c p m p + h( A + PR ( H y) ) Calculate smoke layer density by ρ s = 353/ T s Calculate the pressure difference at floor leel by A N ( α ) 2 2 / 2ρ D p = m p A Required area of natural ent opening = m p/ α 2ρ End { p + ( ρ ρ ) g( H y) } Fig. 6: The calculation procedure of natural smoke ent systems N d. Hybrid smoke management system design When the natural smoke ent demands excessie space or the mechanical smoke exhaust rate becomes too huge, a combination of the two can be designed to become a hybrid smoke management system. It allows more flexibility to the designer and proides an important option for system optimization. The smoke descending rate of a hybrid system can be calculated as: d A ( ρ( H y) ) dt = m p m ext 2.4 Eacuation Analysis n m (6) In ealuating RSET, the humane interention and response of each time step during eacuation has to be considered. Normally, the RSET can be represented as: RSET = t + t + t + t + t (7) d a o i RSET = the required egress time needed to a safety place (s) t d = time of fire being detected after ignition (s) t a = time when alarm was actuated after detection (s) t o = eacuees response time to an alarm (s) t i = time elapsed before eacuation actually takes place (s) t t = actual eacuation time needed for the whole crowd leading to a safety place (s) The actual eacuation time t t can be ealuated mainly by two calculation models. One is the Steady State-Steady Flow (SSSF) model. Conentionally, the SSSF model is used in considering the eacuation process being similar to a hydraulic flow [13]. The total egress time needed is the larger of the walking time needed from the farthest exit or the time needed to pass through exits. Or, T 1 = max (t 11,t 12 ) (8) T 1 = egress time (s) t 11 = walking time needed to the farthest exit (s) d t 11 = (9) t 186

7 d = traeling distance from the most remote point (m) = unimpeded walking elocity (ms -1 ) t 12 = time needed to pass through exits (s) N t12 = (1) n b N = effectie eacuee number (-), persons n = eacuation flow rate (persons/m-s) B = effectie exit width (m) Howeer, in certain occasions, the SSSF model oer-simplified the eacuation phenomenon, especially in a huge crowd bottleneck is ery likely to form and the dynamic egress model should be used instead. The dynamic egress analysis, in simulating indiiduals to eacuate on a computer screen, considers more profoundly the crowd moement diersity, stairs and exists aailability and human behaior. A number of computer eacuation models hae been deeloped in an attempt to predict the egress process. Most of these are based on network-node approaches, such as EVACNET+, EXITT, EXIT89. On the other hand, the models which use spatial analysis techniques to define the moement of crowds and to track the trajectory of all indiiduals as they make their way out of the enclosure hae become ery popular recently. These models include SIMULEX, EXDOUS, EGRESS, STEPS. The computer model SIMULEX is designed to simulate the egress moement of thousands of indiidual people in large, geometrically complex, multi-story building spaces. Thompson and Marchant [14] carried out a lot of tests to ealuate the maximum sustainable exit flow rate through different passageways indicated that SIMULEX simulation results could correlate well to the data obtained from real-life obserations. The authors [15] also performed seeral alidations of the SIMULEX application to geometrically complex building designs (such as underground rail stations, shopping malls, etc.) with successful results. Therefore, the SIMULEX program was utilized for design analysis in this study. 2.5 Quantitatie Risk Assessment The performance-based fire safety design is normally relied on the what-ifs, or the worst-case scenario which is probabilistic in nature. During the whole emergency procedure, each step takes some time to complete and the time needed is dependent on the technical specification in each subsystem designed. The smoke management system should maintain at least the whole time period to proide a smoke-free escape route. Howeer, the fire and smoke detectors, the annunciation, and the human reaction in the control center or the eacuees response could be so different and heaily dependent on the occurring fire sizes, fire location and een unknown reasons. For example, the beam-type smoke detection system may be specified to actiate in 6 s when a fire occurs, but it could only take 3 s to react properly if the fire occurred right underneath, or ice ersa. The human factor also plays a similar role in identifying a fire and calling the control center, or in directing the eacuee during the egress process. To consider the uncertainties and probabilities in each time step, the Monte Carlo method was adapted in this study. Each time step was assigned a normal distribution cure with the maximum occurrence probability assigned according to its engineering specifications. Therefore, in simulation process, the beam detectors not only responded in 6 s as they are specified by the designers, but could also react in 5 s, 4 s and 3 s, etc. only in reducing probabilities. The objecties of Quantitatie Risk Assessment (QRA) using Monte Carlo simulation are to calculate the combined impact of the model s arious uncertainties when a building caught fire, in order to determine a probability distribution of the total egress time. It is adapted as a power tool to ealuate the effectieness of the designed emergency procedures. 3. DESIGN CASE STUDY The authors hae recently completed a performance-based fire safety design project following the procedure deeloped in this paper and is discussed here for demonstration purpose. This project is designed for a modern shopping mall, which is twele floors aboe ground for retail shops and seen floors underground for small delicatessen restaurants and car parks. Fig. 7 shows the profile of the CP shopping mall, Table 3 listed the dimension of the two atria under study. Table 3: Geometry of the two atria Atrium I Atrium II Length 69.5 m 12 m Width 15 m 12 m Height 73.6 m 31.2 m The atrium under consideration is 69.5 m in height, which is well oer the 8 m (25 ft) limit as 187

8 recommended in NFPA 92B for sprinkler system installation at the top. So that, in this case, the atrium did not install a sprinkler fire suppression system. On the other hand, the sprinkler system was indeed installed on each retail floor based on the local Fire Safety Code. So that, the design fire size of 5 MW, fast-t 2 fire growth cure was specified in calculation to be conseratie. Redundant beam detectors hae been adapted for quick response and for eliminating false alarms. The smoke-and-heat hybrid type detectors were installed as another redundancy. Human identification of a fire was considered a must before the automatic emergency procedure was launched. The smoke management system design needs further discussion. In order to simulate the smoke descending rate of Atrium I, both zone model and 3D CFD model consisting of 5, grid cells were used. The simulation result shown in Fig. 8 indicated that the natural smoke filling process takes about 8 s to complete. Fig. 9 shows the intermediate stages of temperature and elocity distributions ceiling jet creates a large eddy and turbulence causing the smoke to descend quickly. To control the smoke in an acceptable clear height, it is proposed to isolate the 1th to 12th (1F~12F) floor atrium connecting space with fire-proof wire-meshed glass block so that the atrium space can be sered as a smoke storage space. The designed smoke clear height is thus 55.2 m aboe the ground, or at the bottom of the 1th floor. In NFPA 11 Life Safety Code [16], 4 to 6 ACH (Air Change Rate per hour) was recommended as an effectie smoke exhaust rate of a large space. Howeer, the correspondingly large exhaust rate, or 128 m 3 s -1 in this case, can only keep the clear height at 19.1 m but not the 55.2 m needed in such a tall atrium. The tremendous atrium height results in a huge smoke generation rate and should not be taken care of by mechanical smoke exhaust system only. Proposals were made to either adapt partial natural ent system and/or intersect the atrium in half in the middle two smoke zones were created so that feasible mechanical smoke exhaust system can be installed maintaining tenable conditions within 48 s and holding smoke leel there steadily. Fig. 1 shows the successful simulation result of Atrium II in the spherical building following these design concepts. This atrium is diided into two smoke zones by fire-proof partition, so that atrium II in the spherical building with 31.2 m height is easier to tackle with. When 1 m 3 s -1 mechanical exhaust system was designed, the smoke position was held at the 7th floor (7F) at around 74 s, and further descending to the 6th floor (6F) at 2 s, and held there steadily. This is considered a tenable condition. To sum up, the smoke management system of this project has been designed through this procedure to maintain the tenable condition. Fire-proof partition Atrium I Atrium II Fig. 7: Profile of the CP shopping mall 188

9 Smoke Clear Height (m) Smoke Natural Filling Mechanical Exhaust (71 cms) Mechanical Exhaust (128 cms (6ACH)) CFD Simulation (Smoke Natural Filling) Time (sec) Fig. 8: Predicted smoke-layer positions in Atrium I Fig. 9: Predicted air flow pattern and temperature distribution in Atrium I 3 Smoke Natural Filling Mechanical Exhaust(1 cms) 25 CFD Simulation Smoke Clear Height (m) Time (sec) Fig. 1: Predicted smoke-layer positions in Atrium II 189

10 In order to ealuate the required safe egress time, or RSET, dynamic egress analysis using SIMMULEX [17] has been performed and compared with the SSSF model. Based on the local fire code, any exit should be located in less than 3 m from any spot of the building interior. Based on a full-scale experiment performed by the authors [18], and compared with SFPE data [13], the eacuation walking elocity and flow rate was selected. Based on the SSSF model, a fixed constant of 1.3 persons/s-m was assumed as the exit flow rate as shown in Table 4. It is interesting to simulate this flow rate using a dynamic model, so that a more accurate result could be obtained, while maintaining the simplicity of the SSSF model as shown in case 2 of Table 4. Or, a thorough dynamic egress analysis was performed to calculate the total eacuation time as shown in case 3 of Table 4. Comparison of Table 4 results in the fact that in a crowded shopping mall accommodating more than 2 people, the SSSF model sometimes oer-simplifies in calculating the eacuation time needed by oer 5%, and the dynamic egress simulation model should be used instead. Fig. 11 emphasized this point further, that the flow rate constant actually decided the slope of the eacuation line in the SSSF model. Howeer, the dynamic model depicted that this cure is hardly a straight line at all, and the deiation between the two models becomes obious. The total eacuation time calculated, or t t in equation (7) is 257 s. As listed in Table 5, the RSET in this case is 377 s. Table 4: Total eacuation time predicted by SSSF model and dynamic model Parameter Case 1 Case 2 Case 3 Occupancy density.5 person/m 2 SSSF model (1.3 persons/s-m) SSSF model (SIMULEX simulated flow rate) Total floor area m 2 t1 t2 t1 t2 Dynamic simulation Total eacuees s No. of exits 8 = s = 11.5 s = s = s Total width of exits 14. m 11.5 s s s 25 Simulex Simulation 1.3 person/s-m.57 person/s-m accumulated Accumulated eacuees Eacuees Trael time (sec) Fig. 11: Comparison of the eacuation cure predicted by dynamic model with the SSSF model on the 11th floor of Atrium I 19

11 Fig. 12: Simulation result of Quantitatie Risk Analysis using Monte Carlo simulation in Atrium I Table 5: Mean RSET on the 11th floor in the Atrium I Fire and/or smoke detection Identification of fire location Alarm and announcement Egress route selection Egress in process RSET Aerage time 6 s 2 s 3 s 1 s 257 s 377 s When one remembered that the smoke management system in this project has been designed to maintain the smoke-free escape route, or tenable condition, for more than 12 mins (ASET), the safety factor of smoke management and egress design in this project is approximately 2. Quantitatie risk assessment has been performed which alidated the effectieness of the whole emergency procedure as shown in Fig. 12. That is, the most probable time needed for the emergency process to complete is 375 s, or 525 s in the worst case. On the other hand, the tenable condition can be maintained by smoke management systems for 12 mins (72 s), which warranted the effectieness of the complete emergency procedure. 4. CONCLUSIONS The performance-based design procedure as deeloped in this study consists of the integration of a smoke detection and management system with the egress planning to maintain a smoke-free tenable escape route. The effectieness of the complete emergency procedure has been analyzed with quantitatie risk assessment and demonstrated in a modern shopping mall design successfully. To this end, a more flexible, safer, and cost- effectie fire safety engineering design methodology can be achieed. NOMENCLATURE Symbols A area of building floor (m 2 ) a fire growth rate A D door way area (m 2 ) A f area of fire source (m 2 ) A i total area of all inlets (m 2 ) A N smoke ent area (m 2 ) A measured throat area of entilators (m 2 ) A W area (m 2 ) b effectie exit width (m) C i entry coefficient for all inlets (typically about.6) c p specific heat of air (kjkg -1 K -1 ) C coefficient of discharge (usually between.5 and.7) D fire diameter (m) d trael distance from most remote point (m) D B depth of smoke beneath entilator (m) g acceleration of graity (ms -2 ) H height of building (m) h total heat transfer coefficient (kwm -2 k -1 ) H N height of smoke ent (m) L mean flame height (m) N effectie eacuee number (-), persons n eacuation flow rate (persons/m-s) P fire perimeter (m) P R perimeter length of the room (m) Q total heat release rate (kw) N effectie eacuee number (-) Q c conectie portion of the heat release rate (Btus -1 ) T temperature (K) t time (s) 191

12 t T 1 t 11 t 12 effectie ignition time (s) egress time (s) walking time needed to the farthest exit (s) time needed to pass through exits (s) unimpeded walking elocity (ms -1 ) y smoke layer position (m) Z height aboe fuel surface (m) Z m maximum height of smoke rise aboe fire surface (m) α opening flow coefficient T / dz rate of change of ambient temperature with respect to height (C/m) ρ density (ms -2 ) 2 2 Q /[ c T ( gd) ] 1/ D * D ρ (-) Q p m ext extraction rate of mechanical exhaust system (kgs -1 ) n m mass flow rate of smoke to be extracted (kgs -1 ) p m plume mass flow rate (kgs -1 ) p pressure difference at the leel of the floor (pa) T s temperature rise of smoke layer aboe ambient (C) Subscripts fl flames centerline ambient s smoke layer REFERENCES 1. Fire Safety Code, Ministry of Interior, Republic of China (1999) - In Chinese. 2. NFPA 92B, Guide for smoke management systems in malls, atria, and large areas, National Fire Protection Association (1995). 3. H.P. Morgan, Smoke control methods in enclosed shopping complexes of one or more storys: A design summary, Building Research Establishment Report (1979). 4. P.I.A.R.C., Technical Committee on Road Tunnels Report, Permanent International Association of Road Congresses Report No. 5, XVIIIth World Road Congress, Brussels, September (1987). 5. V. Babrauskas, Burning rates, The SFPE Handbook of Fire Protection Engineering, Society of Fire Protection Engineering (1995). 6. G. Heskestad, Fire plume air entrainment according to two competing assumptions, 21th Symposium on Combustion, The Combustion Institute, pp (1986). 7. P.H. Thomas et al., Inestigations into the flow of hot gas in roof enting, Fire Research Technical Paper No. 7, Department of Scientific and Industrial Research and fire Offices Committee, Joint Fire Research Organization, London (1963). 8. B.M. Cetegen, E.E. Zukoski and T. Kubota, Entrainment in the near and far field of fire plumes, Combustion Science and Technology, Vol. 39, pp (1984). 9. B.J. McCaffrey, Momentum implications for buoyant diffusion flames, Combustion and Flame, No. 52 (1983). 1. T. Tanaka and T. Yamana, Smoke control in large scale spaces, (Part 2: Smoke control in large scale spaces), Fire Science and Technology, Vol. 5, No. 1, pp (1985). 11. G.D. Lougheed, Personal communication, National Research Council of Canada, 2 March (1991). 12. H.P. Morgan and J.P. Gardner, Design principles for smoke entilation in enclosed shopping centers, Building Research Establishment Report No. 186 (199). 13. H.E. Nelson and H.A. MacLennan, Emergency moement, The SFPE Handbook of Fire Protection Engineering, Society of Fire Protection Engineering (1995). 14. P.A. Thompson and E.W. Marchant, Testing and application of the computer model SIMULEX, Fire Safety Journal, Vol. 24, pp (1995). 15. K.H. Yang and S.K. Lee, Smoke management and egress design analysis of an underground railway station, To be appeared in The Journal of Applied Fire Science (2). 16. NFPA 11, Life Safety Code, National Fire Protection Association (1995). 17. P.A. Thompson and E.W. Marchant, A computer model for the eacuation of large building populations, Fire Safety Journal, Vol. 24, pp (1995). 18. K.H. Yang and T.C. Yeh et al., An experimental inestigation on smoke management in Taipei Rapid Transit Systems, International Conference of Mass Transit Management, Kuala Lumpur, Malaysia (1997). 192