analysis of performance-based smoke … of performance-based smoke management system ... abstract in...

International Journal on Architectural Science, Volume 1, Number 4, p.181-192, 2000

181

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 University, Kaohsiung, Taiwan 80424, R.O.C. (Received 20 September 2000; Accepted 16 November 2000) ABSTRACT In Taiwan, the fire code is still prescriptive in nature which fails to provide effective design guide for buildings with large spaces and atria. In this paper, the NFPA 92B has been adapted to develop a design procedure of smoke management system in a shopping mall atrium using performance-based fire safety design method. The objectives of this design procedure are assurance of safe evacuation and prevention 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 approval from authorities having 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 prescriptive fire code was implemented in Taiwan [1]. On item 189, No. 7, it stated that the smoke exhaust rate should not be less than 120 m3min-1. And in zoned smoke control designs, each zone should be equipped with mechanical smoke exhaust rate for more than 1 m3min-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 deviation could be up to 6 times. The deviation lies mainly in that the prescriptive code ignored the large air entrainment volume of an atrium when a fire occurred, although it still serves 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 500 m2 room (5 MW fire)

Design smoke clear height

NFPA 92B Taiwan Fire Code

1.5 m 5.35 m3s-1 8.33 m3s-1 2.0 m 7.13 m3s-1 8.33 m3s-1 2.5 m 8.92 m3s-1 8.33 m3s-1 5.0 m 18.52 m3s-1 8.33 m3s-1

10.0 m 47.08 m3s-1 8.33 m3s-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 • Evacuation Analysis, and • Quantitative 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 evaluation 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 20 MW to 30 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, where the heat release rate is directly proportional to the square of time elapsed, or in equation form:

20 )( ttaQ −= (1)

where

International Journal on Architectural Science

182

Start

Design Fire Size

BuildingGeometry

Fire Detection &Suppression System

Design

Evacuation Smoke ManagementSystem Design

ASET>RSET

QuatitativeRisk

AsessmentMechanicalVentilation

NaturalVentilation

HybridVentilation

HumaneBehavior

End

Modify thenumber or Width

of ExitsModify SmokeExtraction Rate

NoNo

Yes

To compile theintegrated emergency

procedure

Fig. 1: Flow chart of performance-based fire safety design method

Q = heat release rate or the fire size in kw t0 = effective ignition time t = actual time elapsed a = fire growth rate In NFPA 92B, four different types of t2-fire were assumed as shown in Fig. 2. The designer has to choose one which fits well with the project under investigation. Sometimes a full-scale test should be arranged to validate the assumption, such as a wet-bench fire of a semi-conductor clear room, or an actual carriage fire set inside a vehicle tunnel.

c. Measured fire growth

A measured fire growth curve is utilizing test data from Cone-Calorimetry, a bench-scale test or a full-scale test, and curve-fitted to represent the “actual” heat release rate [5]. The curves 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 provides 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:

( ) 3/81/4 /5.54 −∆= dzTQz cm (2) where Zm = maximum height of smoke rise above fire surface (m) Qc = convective 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 activated in an atrium, the water droplet could


183

Fig. 2: Relation of t-squared fires to some fire tests

be evaporated so quickly and becoming water mist before hitting the fire source. An actual fire occurred several 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 achieved by designing mechanical and natural venting systems. But before that, the natural smoke filling process should be evaluated.

a. Smoke filling process evaluation

In order to evaluate the available safety egress time (ASET), the smoke filling of the atrium and the smoke descending rate can be calculated by:

( )( )pm

dtyHdA

⋅=

−ρ (3)

During the natural smoke filling process, the smoke descending rate is closely related to the fire plume air entrainment mass flow rate, where 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 various heights of a 5 MW fire. This figure depicts that the smoke

mass flow rate calculated by the CFAST plume model is obviously too high, could be 92.5% higher than that calculated by the NFPA 92B plume model at the atrium height of 30 m. In Fig. 4, the BRI (Building Research Institute, Japan) [10] 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 above, 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 ( pm⋅

).

3. Size the smoke exhaust system capacity where

pext mm⋅⋅

≥ .

The smoke descending rate of an atrium can thus be calculated by:

( )( )extp mm

dtyHdA

⋅⋅−=

−ρ (4)


184

Table 2: Formula of fire plume air entrainment mass flow rate

Heskstad (NFPA 92B)

Flame region: ( )vcp zzQm −=⋅

3/5032.0

Plume region: ( ) ( )[ ]3/53/23/53/1 026.01071.0 −⋅

−+−= vcvcp zzQzzQm

Virtual origin: 5/2083.002.1 QDzv +−=

Flame Height: 5/2166.0 cQL = McCaffrey (CFAST)

Flame region: 08.000.0011.0 5/2

566.0

5/2 <

≤

=

⋅

Qz

Qz

Qm p

Intermittent region: 20.008.0026.0 5/2

909.0

5/2 <

≤

=

⋅

Qz

Qz

Qm p

Plume region:

≤

=

⋅

5/2

895.1

5/2 20.0124.0Q

zQ

zQ

m p

Thomas et al. Flame region: ( ) ( ) 2/32/1/096.0 vflp zzPgm −= ∞∞

⋅ρρρ

Plume region: ( ) ( ) 3/53/10 /153.0 vpp zzTcQgm −= ∞

⋅ρ

Virtual origin: 2/15.1 fv Az = Zukoski et al.

Plume region: ( ) ( ) 3/53/13/12 /21.0 vpp zzQTcgm −= ∞∞

⋅ρ

Virtual origin: With floor: LDzv 33.050.0 +−= Without floor: LDzv 33.080.0 +−= Flame Height :

3/2** 30.3/:0.1 DD QDLQ =< 5/2** 30.3/:0.1 DD QDLQ =≥

where [ ]22/1* )(/ DgDTcQQ pD ∞∞= ρ

0 5 10 15 20 25 300

50

100

150

200

250

300

350

400

450

500

550

600

650

700 Zukoski Plume model NFPA 92B Plume model McCaffrey Plume model

entra

inm

ent m

ass f

low

rate

(kg/

s)

Clear Height (m)

Fig. 3: Fire plume air entrainment mass flow rate under various heights of a 5 MW fire

Entra

inm

ent M

ass F

low

Rat

e (k

gs-1

)


185

0 100 200 300 400 500 600 700 800 900 1000 1100 12000

2

4

6

8

10

12

14

16

18

20

22

24

26

28 NFPA Plume model Zukoski Plume model NRCC data BRI data

Smok

e C

lear

Hei

ght (

m)

Time (sec) Fig. 4: Comparison of the predictions of smoke-layer position with the experimental data

0 50 100 150 200 250 300 350 400 450 500 550 6000

5

10

15

20

25

30 Visual in BRI test Judged by Temperature Measurements in BRI test NFPA 92B Plume Model in BRI Test Judged by Temperature Measurements in this study Visual in this study Video in this study NFPA 92B Plume Model in this study

Smok

e C

lear

Hei

ght(m

)

Time(sec) Fig. 5: Comparison of the predictions of smoke-layer position with experimental data for

the case with mechanical ventilation of 6 m3s-1

Fig. 5 shows the validation of this model by a full-scale experiment performed by BRI (Building Research Institute, Japan) [10] with mechanical smoke exhaust rate of 6.0 m3s-1. At the early 80 s, the predicted smoke clear height is lower than that measured since the time lag is not counted effectively. 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 visually with a video-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 ventilation system design

The smoke management system can be optimized, if natural and mechanical smoke exhaust were combined into a hybrid system, where exhaust fans can be downsized significantly. The natural smoke vent introduces a turbulent air moving process due to high buoyancy and thus heavily depends on smoke layer temperature and


186

thickness. In our designs, natural smoke exhaust rate was calculated using Morgan’s experimental equation [12], or:

( ) 2/122

2/

∆+

=∞

∞

∞

⋅

TTgDTTCACATmCA

sB

siivvsnvv ρ

(5)

where Av = measured throat area of ventilators (m2) Ai = total area of all inlets (m2) Ci = entry coefficient for all inlets (typically about 0.6) Cv = coefficient of discharge (usually between 0.5 and 0.7) DB = depth of smoke beneath ventilator (m) g = acceleration of gravity (ms-2)

⋅

nm = mass flow rate of smoke to be extracted (kgs-1)

sT = absolute temperature of smoke layer (K)

∞T = absolute temperature of ambient air (K)

sT∆ = temperature rise of smoke layer above 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

( )

−++

+=⋅∞

)( yHPAhmc

QTTRpp

s

Calculate smoke layer density by

ss T/353=ρ

Calculate the pressure difference at floor level by

( )22 2/ Dp Amp αρ∞

⋅=∆

Required area of natural vent

opening

( ) ( ){ }yHgpmA NpN −−+∆−= ∞

⋅ρρρα 2/

End

Fig. 6: The calculation procedure of natural

smoke vent systems

d. Hybrid smoke management system design

When the natural smoke vent demands excessive 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 provides an important option for system optimization. The smoke descending rate of a hybrid system can be calculated as:

( )( )nextp mmm

dtyHdA

⋅⋅⋅−−=

−ρ (6)

2.4 Evacuation Analysis In evaluating RSET, the humane intervention and response of each time step during evacuation has to be considered. Normally, the RSET can be represented as:

tioad tttttRSET ++++= (7) where RSET = the required egress time needed to a safety place (s) td = time of fire being detected after ignition (s) ta = time when alarm was actuated after detection (s) to = evacuees’ response time to an alarm (s) ti = time elapsed before evacuation actually takes place (s) tt = actual evacuation time needed for the whole crowd leading to a safety place (s) The actual evacuation time tt can be evaluated mainly by two calculation models. One is the Steady State-Steady Flow (SSSF) model. Conventionally, the SSSF model is used in considering the evacuation 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, T1 = max (t11,t12) (8) where T1 = egress time (s) t11 = walking time needed to the farthest exit (s)

vdt =11 (9)

where


187

d = traveling distance from the most remote point (m) v = unimpeded walking velocity (ms-1) t12 = time needed to pass through exits (s)

bnNt×

=12 (10)

where N = effective evacuee number (-), persons n = evacuation flow rate (persons/m-s) B = effective exit width (m) However, in certain occasions, the SSSF model over-simplified the evacuation phenomenon, especially in a huge crowd where bottleneck is very likely to form and the dynamic egress model should be used instead. The dynamic egress analysis, in simulating individuals to evacuate on a computer screen, considers more profoundly the crowd movement diversity, stairs and exists availability and human behavior. A number of computer evacuation models have been developed 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 movement of crowds and to track the trajectory of all individuals as they make their way out of the enclosure have become very popular recently. These models include SIMULEX, EXDOUS, EGRESS, STEPS. The computer model ‘SIMULEX’ is designed to simulate the egress movement of thousands of individual people in large, geometrically complex, multi-story building spaces. Thompson and Marchant [14] carried out a lot of tests to evaluate the maximum sustainable exit flow rate through different passageways indicated that SIMULEX simulation results could correlate well to the data obtained from real-life observations. The authors [15] also performed several validations 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 Quantitative 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 provide a smoke-free escape route. However, the fire and smoke detectors, the annunciation, and the human reaction in the control center or the evacuees’ response could be so different and heavily dependent on the occurring fire sizes, fire location and even unknown reasons. For example, the beam-type smoke detection system may be specified to activate in 60 s when a fire occurs, but it could only take 30 s to react properly if the fire occurred right underneath, or vice versa. The human factor also plays a similar role in identifying a fire and calling the control center, or in directing the evacuee 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 curve with the maximum occurrence probability assigned according to its engineering specifications. Therefore, in simulation process, the beam detectors not only responded in 60 s as they are specified by the designers, but could also react in 50 s, 40 s and 30 s, etc. only in reducing probabilities. The objectives of Quantitative Risk Assessment (QRA) using Monte Carlo simulation are to calculate the combined impact of the model’s various 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 evaluate the effectiveness of the designed emergency procedures. 3. DESIGN CASE STUDY

The authors have recently completed a performance-based fire safety design project following the procedure developed in this paper and is discussed here for demonstration purpose. This project is designed for a modern shopping mall, which is twelve floors above ground for retail shops and seven floors underground for small delicatessen restaurants and car parks. Fig. 7 shows the profile of the CP shopping mall, where 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 over the 8 m (25 ft) limit as


188

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-t2 fire growth curve was specified in calculation to be conservative. Redundant beam detectors have 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 50,000 grid cells were used. The simulation result shown in Fig. 8 indicated that the natural smoke filling process takes about 800 s to complete. Fig. 9 shows the intermediate stages of temperature and velocity distributions where 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 10th to 12th (10F~12F) floor atrium connecting space with fire-proof wire-meshed glass block so that the atrium space can be served as a smoke storage space. The

designed smoke clear height is thus 55.2 m above the ground, or at the bottom of the 10th floor. In NFPA 101 Life Safety Code [16], 4 to 6 ACH (Air Change Rate per hour) was recommended as an effective smoke exhaust rate of a large space. However, the correspondingly large exhaust rate, or 128 m3s-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 vent system and/or intersect the atrium in half in the middle where two smoke zones were created so that feasible mechanical smoke exhaust system can be installed maintaining tenable conditions within 480 s and holding smoke level there steadily. Fig. 10 shows the successful simulation result of Atrium II in the spherical building following these design concepts. This atrium is divided 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 100 m3s-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 200 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.

Fig. 7: Profile of the CP shopping mall

Atrium I

Atrium II

Fire-proof partition


189

0 100 200 300 400 500 600 700 800 900 1000 1100 120005

101520253035404550556065707580

Smoke Natural Filling Mechanical Exhaust (710 cms) Mechanical Exhaust (128 cms (6ACH)) CFD Simulation (Smoke Natural Filling)

Smok

e C

lear

Hei

ght (

m)

Time (sec)

Fig. 8: Predicted smoke-layer positions in Atrium I

Fig. 9: Predicted air flow pattern and temperature distribution in Atrium I

0 50 100 150 200 250 3000

5

10

15

20

25

30 Smoke Natural Filling Mechanical Exhaust(100 cms) CFD Simulation

Smok

e C

lear

Hei

ght (

m)

Time (sec) Fig. 10: Predicted smoke-layer positions in Atrium II


190

In order to evaluate 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 30 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 evacuation walking velocity 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 evacuation 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 2000 people, the SSSF model sometimes over-simplifies in calculating the evacuation time needed by over 50%, 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 evacuation line in the SSSF model. However, the dynamic model depicted that this curve is hardly a straight line at all, and the deviation between the two models becomes obvious. The total evacuation time calculated, or tt in equation (7) is 257 s. As listed in Table 5, the RSET in this case is 377 s.

Table 4: Total evacuation time predicted by SSSF model and dynamic model

Parameter Case 1 Case 2 Case 3

Occupancy density

0.5 person/m2 SSSF model (1.3 persons/s-m)

SSSF model (SIMULEX simulated

flow rate)

Dynamic simulation

Total floor area 4585.87 m2 t1 t2 t1 t2

Total evacuees 2012 3.18.29

143.12012×

3.18.29

1457.02012

×

No. of exits 8 = 22.92 s = 110.5 s = 22.92 s = 252.1 s

256.4 s

Total width of exits

14.0 m 110.5 s 252.1 s 256.4 s

0 50 100 150 200 250 3000

500

1000

1500

2000

2500

Simulex Simulation 1.3 person/s-m 0.57 person/s-m

accu

mul

ated

eva

cuee

s

Travel time (sec)

Fig. 11: Comparison of the evacuation curve predicted by dynamic model with the SSSF model on the 11th floor of Atrium I

A

ccum

ulat

ed E

vacu

ees


191

Fig. 12: Simulation result of Quantitative Risk Analysis using Monte Carlo simulation in Atrium I Table 5: Mean RSET on the 11th floor in the Atrium I

Average time

Fire and/or smoke detection 60 s Identification of fire location 20 s Alarm and announcement 30 s Egress route selection 10 s Egress in process 257 s RSET 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. Quantitative risk assessment has been performed which validated the effectiveness 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 (720 s), which warranted the effectiveness of the complete emergency procedure. 4. CONCLUSIONS The performance-based design procedure as developed 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 effectiveness of the complete emergency procedure has been analyzed with quantitative risk assessment and demonstrated in a modern shopping mall design successfully. To this end, a more flexible, safer, and cost-

effective fire safety engineering design methodology can be achieved. NOMENCLATURE Symbols A area of building floor (m2) a fire growth rate AD door way area (m2) Af area of fire source (m2) Ai total area of all inlets (m2) AN smoke vent area (m2) Av measured throat area of ventilators (m2) AW area (m2) b effective exit width (m) Ci entry coefficient for all inlets (typically about

0.6) cp specific heat of air (kJkg-1K-1) Cv coefficient of discharge (usually between 0.5

and 0.7) D fire diameter (m) d travel distance from most remote point (m) DB depth of smoke beneath ventilator (m) g acceleration of gravity (ms-2) H height of building (m) h total heat transfer coefficient (kwm-2k-1) HN height of smoke vent (m) L mean flame height (m) N effective evacuee number (-), persons n evacuation flow rate (persons/m-s) P fire perimeter (m) PR perimeter length of the room (m) Q total heat release rate (kw) N effective evacuee number (-) Qc convective portion of the heat release rate

(Btus-1) T temperature (K) t time (s)


192

t0 effective ignition time (s) T1 egress time (s) t11 walking time needed to the farthest exit (s) t12 time needed to pass through exits (s) v unimpeded walking velocity (ms-1) y smoke layer position (m) Z height above fuel surface (m) Zm maximum height of smoke rise above fire

surface (m) α opening flow coefficient

dzT /∆ rate of change of ambient temperature with respect to height (C/m)

ρ density (ms-2) *DQ [ ]22/1)(/ DgDTcQ p ∞∞ρ (-) ⋅

extm extraction rate of mechanical exhaust system (kgs-1)

⋅

nm mass flow rate of smoke to be extracted (kgs-1)

⋅

pm plume mass flow rate (kgs-1) p∆ pressure difference at the level of the floor

(pa) sT∆ temperature rise of smoke layer above

ambient (C) Subscripts fl flames 0 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, 13-19 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. 111-120 (1986).

7. P.H. Thomas et al., Investigations into the flow of hot gas in roof venting, 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. 305-331 (1984).

9. B.J. McCaffrey, “Momentum implications for buoyant diffusion flames”, Combustion and Flame, No. 52 (1983).

10. 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. 41-54 (1985).

11. G.D. Lougheed, Personal communication, National Research Council of Canada, 20 March (1991).

12. H.P. Morgan and J.P. Gardner, Design principles for smoke ventilation in enclosed shopping centers, Building Research Establishment Report No. 186 (1990).

13. H.E. Nelson and H.A. MacLennan, Emergency movement, 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. 149-166 (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 (2000).

16. NFPA 101, Life Safety Code, National Fire Protection Association (1995).

17. P.A. Thompson and E.W. Marchant, “A computer model for the evacuation of large building populations”, Fire Safety Journal, Vol. 24, pp. 131-148 (1995).

18. K.H. Yang and T.C. Yeh et al., “An experimental investigation on smoke management in Taipei Rapid Transit Systems”, International Conference of Mass Transit Management, Kuala Lumpur, Malaysia (1997).

analysis of performance-based smoke … of performance-based smoke management system ... abstract in...

Documents