THE COMBINATION OF FIRE EXTINGUISH SYSTEM AND LOCAL EXHAUST SYSTEM IN FUME HOOD

THE COMBINATION OF FIRE EXTINGUISH SYSTEM AND LOCAL EXHAUST SYSTEM IN FUME HOOD S.K. Lee 1, S.Y. Lin 1, T.C. Ko 1, and M.C. Teng 1 Department of Safety, Health, and Environmental Engineering, National Kaohsiung First University of Science and Technology, Kaohsiung, Taiwan National Science and Technology Center for Disaster Reduction ABSTRACT Working with volatile chemicals creates numerous hazards for scientists in laboratory. Therefore, it is restricted to do such works in a fume hood, which is designed to draw fresh air from the room into the hood and then out into the ventilation system, in order to prevent the accidents happened. According to the laboratory fire incidents investigation, the authors observed that a fire occurred in fume hood will be a serious problem which has the potential to get much worse in the future as more and complex laboratories are used and as the hood usage density increase. In this paper, the authors conducted the numerical experiments by using 3D Computational Fluid Dynamics (CFD) method to evaluate the fire extinguish performance of CO system in fume hood. The simulation results showed that the position of CO nozzle, exhaust air volume, position of sash had a significant effect on fire extinguish in hood. The innovative hybrid system combined fire extinguish system and local exhaust system was designed to ensure the flow pattern in hood could be well-controlled to prevent the contaminant leakage from hood sash as the CO system is activated. KEYWORDS fume hood, fire extinguish system, local exhaust system INTRODUCTION Modern laboratories require comprehensive regulations included temperature, humidity, static pressure, air motion, air cleanliness, exhaust etc. The HVAC system is designed must function as a unit in order to conform to applicable safety and environmental regulations. On the other hand, laboratory research potentially involves hazard. Nearly all laboratories contain some types of hazardous materials. Therefore, the devices such as fume hoods are widespread used in school science laboratories, research, clinical and production labs to protect users to against airborne hazards and toxic contaminant. Most laboratories have design guidelines that incorporate NFPA standard 5 [1], International Code Council s International Mechanical Code (IMC)- [], ASHRAE Application Handbook [3], local government s fire law in design local exhaust system and fire protection system for labs. According to NFPA standard 5: Standard on Fire Protection for Laboratories Using Chemicals, there are two-defining features of a hazardous exhaust system. These features include: 1. Automatic fire protection systems shall not be required in laboratory hoods or exhaust systems. Exception No. 1: Automatic fire protection shall be required for existing hoods having interiors with a flame spread index greater than 5 in which flammable liquids are handled. Exception No. : If a hazard assessment shows that an automatic extinguishing system is required for the laboratory hood, then the applicable automatic fire protection system standard shall be followed.. Automatic fire dampers shall not be used in laboratory hood exhaust systems. Fire detection and alarm systems shall not be interlocked to automatically shut down laboratory hood exhaust fans. Corresponding Author: Tel: + 886-7-611 ext.38, Fax: + 886-7-61161 E-mail address:sklee@ccms.nkfust.edu.tw

It is worth noting that NFPA 5 does not request automatic fire suppression system are installed inherently in fume hood, but fire accidents occurred in laboratory still occur. Therefore, the first purpose of this paper is to categorize the causes that lead 15 laboratory fire accidents in last years. Little research has been done on topic development in fire suppression system for fume hood. Only two types of fire extinguish methods are used in modern laboratory, generally. Method one is to install a CO tank on the top panel of fume hood, as shown in figure 1. The second method is called Firetrace system [] which is an automatic self seeking fire extinguisher, which puts out fire where they start by means of a flexible fire detection and delivery tube. The tube is manufactured from specially produced polymer materials to achieve the desired detection and delivery characteristics. The various extinguishing mediums - AFF Foam, CO, Dry Powder, ABC, Water, Halon 111/131, FM-, Monnex can be used in this system. The second purpose of this paper is to study an innovative fire extinguish system in fume hood concerned on fire suppression performance and indoor air quality. For these objectives to be achieved, the article is structured as follows. The first section is a review of the literature, addressing practical and empirical aspects of the ventilation system for laboratory. This is followed by some background information on the ongoing used fire extinguished system in fume hood. After which laboratory fire case investigation is presented, with full detail statistical results in the research. The third section describes the methodology and grid test for numerical simulation. The simulated results for three case studies are discussed following each of these case descriptive sections. Finally, conclusions are presented and suggestions are made for further research. Figure 1 Roof-typed fire extinguish system Figure FireTrace system Laboratory Fire Case Investigation The information of 15 fire accidents occurred in laboratory reviewed in this work. There were 51 accidents occurred in Taiwan, 38 in China, and the rest of 36 occurred in Europe and America. As indicated in Table 1, fire accidents occurred more frequently in chemical laboratory with 87 cases (69.6%). The second most frequently involved laboratory was physical laboratory ( cases, 17.6%). The remainder accidents (16 cases, 1.8%) occurred in biological laboratory. For a view of fire ignition location, electrical device was the most frequent fire location with 35 cases and desk was the second most frequent fire location with cases as indicated in Table. Hood, Storage place and equipment were the third, the fourth and the fifth most frequent fire location, respectively. This statistic data showed that electrical device is the highest risk potential place in laboratory. For physical and biological laboratory, the operating process is usually more stable than the ones in chemical laboratory, so that the electrical device was the most frequent fire location in such laboratory. However, for chemical laboratory, many inflammable materials were used during experiment process, so that except for electrical device, there were 51 fire accidents (58.6%) occurred at the location of desk, hood and storage place.

To illustrate causes and effects, total fire accidents were classified as four categories, i.e. chemical reaction, static electricity fire, equipment failure fire and fire due to operational error. There are two major causes of chemical reaction fire. The first one is improper control of chemical reaction procedure and the second is flammable material leakage. The major cause of static electricity fire is electric wire overloading. The major cause of equipment failure fire is overheated due to heater failure. The major cause of fire due to operational error is S.O.P. not followed. According to above laboratory fire accidents investigation, we could understand that even most of those fire accidents in laboratory would have been avoided if good fire protection concept is applied in design and safety management program has been implemented, but in real situation the fire is still occurred in laboratory. Therefore, the purpose of this paper is to develop an integrated control algorithm to combine the fire extinguish system and local exhaust system in order to choke the fire immediately, meanwhile the flow pattern in hood could be well-controlled to prevent the contaminant leakage from hood sash as the CO system is activated. Numerical model of Large Eddy Simulation Fire Dynamics Simulator (FDS) [,5] is a 3D computational fluid dynamics model of fire-driven fluid flow. FDS solves numerically a form of the Navier-Stokes equations appropriate for low-speed, thermally-driven flow with an emphasis on smoke and heat transport from fires. FDS has been aimed at solving practical fire problems in fire protection engineering. The physical models included in FDS are described as follows: Cause laboratory Chemical reaction Table1 Cause of fire accidents in laboratory Operational error Static electricity Equipment failure Nature disaster Others biological 7 3 16 chemical 56 9 9 9 1 3 87 physical 5 3 8 Total Table Fire location in laboratory Location Lab desk hood Biosafey hood Storage place Electrical device Equipment chemical 19 1 1 6 biological 1 physical 1 1 11 3 Location Lab Wood cabinet Water tank Exhaust duct Trash can floor chemical 1 biological 1 physical 1 1 1

5 15 1 5 19 1 1 11 1 1 1 6 3 1 Desk Fume hood Biosafety cabinet Storage Electrical device Equipment Wood cabinet Figure 3 Fire source place for laboratories chemical lab biological lab physical lab Hydrodynamic model An approximate form of the Navier-Stokes equations for low Mach number is used in this model. The approximation involves the filtering out of acoustic waves while allowing for large variations in temperature and density and small variation in pressure. This approximation proposed by Rehm and Baum [6] avoid the inefficient and inaccurate problems in most computational algorithms design for compressible flows at low Mach number. Turbulence is treated by means of the Smagorinsky form of Large Eddy Simulation (LES), or Direct Numerical Simulation (DNS) if the underlying numerical grid is fine enough. Details of the hydrodynamics and turbulence model are described as follows: Combustion model The mixture fraction-based combustion model is used in FDS code. The local heat release rate is based on Huggett s relationship of oxygen consumption. "' "' q = H o mo Here, H o is the heat release rate per unit mass of oxygen consumed. m o is the mass burning rate that can be calculated by transforming the oxygen mass conservation equation "' mo DYo ρ = ρd Yo + Dt into an expression for the local heat release rate using the conservation equation for the mixture fraction and the state relation for oxygen. "' m O Yo dyo dyo d = ( ρ D Z) ρd Z = ρd Z dz dz dz DZ the conservation law is showed as: ρ = ρd Z, and the ideal state relation for oxygen is Dt introduced based on the assumption that the chemistry is fast so that fuel and oxidizer cannot co-exist. YO (1 Z / Z f ) Z < Z f Yo ( Z) = Z > Z f In the numerical algorithm, the local heat release rate is computed by first locating the flame sheet, then computing the local heat release rate per unit area, and finally distributing this energy to the grid cells cut by the flame sheet. "'

Thermal Radiation model The Radiation Transport Equation (RTE) for a non-scattering gray gas is s I λ ( = κ( λ) [ I ( x) I( ] where I λ ( is the radiation intensity at wavelength, s is the direction vector of the intensity, κ λ ( x, λ) is absorption coefficient. Due to the spectral dependence can not be solved accurately, the radiation spectrum is divided into a relatively small number of bands in FDS code and the total intensity I λ ( is calculated by summing over all the bands. The band specific RTE s are showed as follows: s I n ( = κ n ( x) [ I b, n ( x) I( ], n = 1KN where I n ( is the intensity integrated over the band n, and κ λ (x) is the appropriate mean absorption coefficient inside the band. The radiant heat flux vector is defined as q r ( x) = si( dω, so that the radiative loss term in the energy equation could be expressed as: qr ( x) = κ( x) [ U ( x) πi b ( x) ]; U ( x) = I( dω π The net radiant energy gained by a grid cell is the difference between that which is absorbed and which is emitted. The source term κ I b is define as κσt / π Outside flame zone κi b = ''' χ r q / π Inside flame zone ''' Here, q is the chemical heat release rate per unit volume and χ r is the local fraction of the energy emitted as thermal radiation. Numerical method In FDS, all spatial derivatives in the governing equations described in the above subsection are discretized by second order central differences on a rectilinear grid and the thermodynamic variables are updated in time using an explicit second order predictor-corrector scheme. The total pressure differential equation formed in Poisson equation is solved efficiently by a direct FFT (Fast Fourier Transform) solver. Grid test It is important consideration to study the influence of the grid resolution on simulation results for any CFD analysis. The choice of grid size should reflect the impact of fire dimension and fire size. For a fire plume, the minimum length scale that must be resolved is the characteristic fire diameter D *, that is /5. * Q D =. According to Quintiere s [7] simulation results, the optimum resolution for flame ρ c pt g height simulation was found to be R*=:5. Above this value, the simulations tend to under-predict the flame height. Below, then the flame height is over-predicted. In addition, it is found that the plume dynamics can only be accurately simulated if the resolution limit is about R*=.1 or smaller. In this paper, the authors not only focus on study the fire plume and flow pattern in hood, but also investigate the face velocity distribution on the hood opening. Therefore, grid test should be performed based on fire plume and face velocity distribution in order to determine the optimal grid resolution for fire simulation in hood. In table 3, the grid test results showed that the face velocity distribution is more smoothly for the case of non-uniform grid setting, and the averaged dace velocity (.51m/ meet the.5m/s±1% criterion in ASHRAE 11. And the simulation cost for the case of non-uniform grid setting is more economic than the case of uniform grid setting. Therefore, we adopt non-uniform grid setting for the numerical simulation in this paper. The grid size in the hood is set as.5m, the size of grid near CO nozzle is set as.1m. On the other hand, we check the resolution of fire plume simulation based on Quintiere s criterion (R*=.1) is.3m. Therefore, it is evident that the numerical experiments performed in this paper could both obey Quintiere s fire plume resolution criterion and face velocity criterion of ASHARE 11 in order to make the accurate results after the grid tests in this study.

Table 3 Simulation results of Grid test Averaged Total Grid Face number velocity (m/ Std. Error for face velocity Grid size =1cm, uniform 3,5..3 Grid size =5cm, uniform 8,.9.8 Grid size =.5cm, uniform,.5.1 Grid size =.5cm, non-uniform 179,.51.1 RESULTS AND DISCUSSION In this section, the authors conducted three numerical experiments to simulate the flow pattern in the hood and to measure the face velocity when a fire was occurred, in order to investigate the optimal ventilation mode both to extinguish the fire and to prevent pollutant leakage. Case1 face velocity variability with fire size in CAV hood In order to investigate the face velocity variability and flow pattern in hood with different fire size, we simulated three different heat release rate of fire as a constant value 31kW 66 kw and 1 kw in case 1, respectively. The ventilation mode used in hood is constant air volume (CAV) system. Four velocity sensors placed at different locations near the opening were used to measure the face velocity. The simulation results were shown in Figure ~6 and Table. The simulated face velocity distribution near opening indicated that the face velocity decreased immediately as fire is ignited, afterwards it was keeping at a constant level. This phenomenon could be explained based on fire dynamics. When a fire is ignited, the hot expansion effect forms a barrier to block fresh air entering through the opening, therefore the face velocity decreased dramatically, consequently the upward hot plume would entrain cold air into fire source through the opening to increase the face velocity approaching a constant level. As shown in table, the mean face velocity also indicated that the mean face velocity is inverse proportional to fire size. The simulation results of case 1 demonstrate that the fire in hood has a significant effect on the ventilation efficiency of CAV system, so that a hood equipped with a CAV system could not prevent the contaminated air from flowing to indoor space in situation of fire. Therefore, it is necessary to use variable air volume (VAV) ventilation system to control the face velocity distribution in order to avoid IAQ problem in laboratory as a fire is occurred in hood. HRR (kw) Table Simulated face velocity for various fire size Mean face velocity (m/ Max. face velocity (m/ Min. face velocity (m/ Std. Err. 31.55.63..39 66.1.57.8.1 1.6.57 -.17.18 Case CAV local exhaust system with typical fire extinguish system In case, we take the effect of fire extinguish system on flow pattern distribution into consideration. We assumed a fire with constant 31kW heat release rate was ignited at 5 second, the typical fire extinguish system with a CO nozzle mounted on the top panel be activated after at 1 second. The CAV local exhaust system with.1 m 3 /s was adopted. The simulated flow pattern illustration as CO nozzle is activated was shown in Figure 7. The simulation result indicated that the most of CO gas were exhausted immediately because the nozzle position was near to exhaust opening. Therefore the typical fire extinguish system with a CO nozzle mounted on the top panel can not put out the fire as shown in Figure 8. On the other hand, the simulated face velocity distribution shown in Figure 9 indicated that the air seems to leak on V and V3 measuring point due to the face velocity were negative. These results among above two cases demonstrated that

a hood equipped with a CAV system could not prevent the contaminated air from flowing to indoor space in situation of fire. Case3 VAV local exhaust system with innovative type extinguish system As can be seen from above simulation results, the face velocity were negative values, indicating no effect on preventing the contaminated air leakage for CAV system. So that, the VAV exhaust system was be used in this case. To evaluate the influence of nozzle position on fire extinguish performance, a few of numerical experiments were performed in order to get an optimal nozzle position where have the most efficient fire extinguish ability. The control parameters are exhaust flow rates and nozzle position. The first stage of simulations involved investigating the required number of nozzle and nozzle position. In order to evaluate the fire extinguish performance, the simulated heat release rate were recorded to estimate the time for heat release rate to decrease to zero. The next part of the investigation was designed for determination the required exhaust flow rate after the fire was ignited in order to prevent burned products from leaking out. During these series of simulations, the authors found that two nozzles installed at each side panel can form a downward CO gas curtain to isolate the air entraining to the fire source, consequently the fire would be extinguished. On the other hand, the authors also found that the exhaust flow rate should be increased after fire occurred. The least exhaust flow rate based on mass balance rule must be more than the summation of the original exhaust flow rate and CO ejecting flow rate in order to avoid the outward leakage..8.7 V 1 V V 3 V.7.6 V 1 V V 3 V Face Velocity(m/.6.5..3. Face Velocity(m/.5..3..1.1. 5 1 15 5 3. 5 1 15 5 3 Figure Face velocity distribution for HRR=31kW Figure 5 Face velocity distribution for HRR=66kW.7.6 V 1 V V 3 V.5 Face Velocity(m/..3..1. -.1 -. 5 1 15 5 3 Figure 6 Face velocity distribution for HRR=1kW Figure 7 The flow pattern illustration in case

5 5 V 1 V V 3 V Heat Release Rate(kW) 35 3 5 15 1 5 Face Velocity(m/ 3 1-1 5 1 15 5 3 Figure 8 Simulated heat release rate of fire in case 5 1 15 5 3 Figure 9 Simulated face velocity distribution in case Figure 1 and 11 summarise the simulated results of heat release rate and face velocity distribution in case3, respectively. The simulated heat release rate shown in figure 1 indicated that the fire could be extinguished as two nozzles were installed at 1/ height, 1/ depth place of side panel in fume hood. The simulated face velocity distribution in case3 is shown Figure 11. This figure shows the response with 3-s delay after exhaust volume was increased to.38m 3 /s. Furthermore, it can be shown that the VAV system can avoid the outward leakage from the fume hood and the face velocity being re-established at it averaged value of.5m/s. Whereas the above analysis has been demonstrated that it is feasible to integrate the local exhaust ventilation system with fire extinguish system in a fume hood in order to achieve the goal of fire safety and indoor air quality, the implications associated with it also could be applied to design consideration for laboratory ventilation system with multiple fume hoods. The following design concepts should be established based on present studied results: 1. The fire detector system should be equipped in fume hood in order to detect a fire occurred during early period of fire growing. The detector installed in hood not only act a rule to active the hood exhaust system, but also link to laboratory alarm system to aware lab staff to put off fire as soon as possible.. The control mode of laboratory ventilation system should be categorized as two modes: normal mode and emergency mode, respectively. The ventilation system supply specified air volume to maintain air quality and thermal comfortable condition in laboratory on normal control mode. As a fire occurred, the ventilation system was be switched to emergency mode. The return air fan should be turned off as a fire is occurred in fume hood, in order to prevent outward leakage from the fume hood when the local exhaust system and fire extinguish system of fume hood are activated by fire detector. 35 Heat Release Rate 5 V1 V V3 V Heat Release Rate(kW) 3 5 15 1 5 Face Velocity(m/ 3 1 5 1 15 5 3 Figure 1 Simulated heat release rate of fire in case 3 5 1 15 5 3 Figure 11 Simulated face velocity distribution in case 3

CONCLUSIONS The information of 15 laboratory fire accidents occurred was reviewed, fire accidents occurred more frequently in chemical laboratory with 87 cases (69.6%). The second most frequently involved laboratory was physical laboratory ( cases, 17.6%). The remainder accidents (16 cases, 1.8%) occurred in biological laboratory. The causes that led to accidents were expressed in a systematic way. In the second phase of this study, the results by using FDS to conduct lots of numerical experiments show that it is feasible to integrate the local exhaust ventilation system with fire extinguish system in a fume hood in order to achieve the goal of fire safety and indoor air quality. Although an effective fire suppression system has investigated in this study, more extensive experiments and measurement would be necessary to make any definite claims along these results. ACKNOWLEDGEMENTS The work described in this paper was fully supported by a grant from the National Science Council, Taiwan, R.O.C. [Project no. 95-1-E-37--1]. REFERENCES 1. NFPA 5 Edition Standard On Fire Protection for Laboratories Using Chemicals, National Fire Protection Association,.. ASHRAE 11, America Society of Heating, Refrigeration and Air Conditioning Engineers, 1995. 3. Metric Version, Industrial Ventilation A Manual of Recommended Practice, 3rd Edition, American Conference of Governmental Industrial Hygienists, pp.1-, ISBN: 1-8817--, 1998. David Gray,An automatic fire-suppression system for the laboratory, Reprinted from American Laboratory News, January. McGrattan, K. B., Baum, H. R., Rehm, R. G., Hamis A., Forney, G. P., Fire Dynamics Simulator User s Manual, NISTIR 669, National Institute of Standards and Technology, Gaithesburg, MD,. 5. McGrattan, K. B., Baum, H. R., Rehm, R. G., Hamis A., Forney, G. P., Fire Dynamics Simulator Technical Reference Guide, NISTIR 6783, National Institute of Standards and Technology, Gaithesburg, MD,. 6. Rehm, R. G., Baum, H. R., The Equations of Motion for Thermally Driven, Journal of Research of the NBS, 83: 97~38, 1978. 7. Ma T. G. and Quintiere J. G., Numerical Simulation of Axi-symmetric Fire Plumes: Accuracy and Limitations, Fire Safety Journal, Vol. 38, pp67~9, 3. 8. McCaffrey B. J., Momentum Implications for Buoyant Diffusion Flames, Combustion and Flame, No. 5, 1983.