ASHRAE CH-06-3-4-2006 Predicting Flashover and Tenability Conditions in Train Fires - A CFD Approach《列车火灾的闪络预测和成立的条件-流体力学计算办法》.pdf
《ASHRAE CH-06-3-4-2006 Predicting Flashover and Tenability Conditions in Train Fires - A CFD Approach《列车火灾的闪络预测和成立的条件-流体力学计算办法》.pdf》由会员分享,可在线阅读,更多相关《ASHRAE CH-06-3-4-2006 Predicting Flashover and Tenability Conditions in Train Fires - A CFD Approach《列车火灾的闪络预测和成立的条件-流体力学计算办法》.pdf(11页珍藏版)》请在麦多课文档分享上搜索。
1、CH-06-3-4 Predicting Flashover and Tenability Conditions in Train Fires-A CFD Approach J. Greg Sanchez, PE Member ASHRAE ABSTRACT This paper presents an approach using commercially available computational fluid dynamics (CFD) software combined with combustion and radiation models to predict the flow
2、, temperature, and smoke concentrationjelds in the event of afire-applied to a train fire scenario. This paper is not a validation but an outline ofkey aspects that need to be included in the modeling. The approach presented here can be used to predictfire growth and determine how long afire would t
3、ake to reach flashover. Although the results presented are for the first 120 seconds only, this short time is suficient to illustrate thefire dynamics predicted using the approach presented here. A comparison with available experimental data for gasoline spills was made. Although used to predict a t
4、rain fire, the approach can be used in any other space such as commercial buildings, hotel atria, and more. INTRODUCTION This paper presents an approach using commercially available computational fluid dynamics (CFD) software to predict fire spread and growth in the event of a train fire-with the us
5、e of combustion and radiation models. This is not a vali- dation paper in which extensive comparison is made with experimental data because very few detailed data are available for train fires. Nevertheless, a comparison with gasoline spill fires was made to serve as a sanity check. Currently, engin
6、eers are trying to learn how to best model fires so that their effects can be accounted for in modern designs in order to protect human life and reduce structural losses. This paper focuses on train fires but the approach can be applied to other areas. This paper is significant in that it is the fir
7、st time this approach has been presented with respect to design applica- tions and train fires. Because ofthe reality ofproject deadlines, designers cannot wait for generally established methods to be developed for each application. Design analysis has to be based on a combination of fundamental phy
8、sics, research, and assumptions. This paper follows in this time-honored tradi- tion. The approach presented accounts for radiation, mass loss, mass available to burn, flammability limits, surface ignition temperature, and fuel vapor auto-ignition temperature, thus the fuel vapors will be able to bu
9、rn when all conditions indi- cate that combustion is possible. The end result is a robust model that is able to predict fire spread and, if allowed to run long enough, can be used to predict whether or not it is possi- ble to reach flashover without prescribing any fire growth profile or heat releas
10、e rate. MOTIVATION FOR THIS PAPER The need to establish a means of predicting fire spread, including flashover, in trains (with complex geometries) has long been needed. ASHRAE Technical Committee 5.9 has been trying to promote research to develop a model with this capability. This is the main reaso
11、n why this paper has focused on train fires-to outline an approach to model the fire dynam- ics in a train fire scenario without prescribing the fire heat release rate. As part of the Memorial Tunnel fire tests (MHD/ FHA 1999), a CFD code was developed with the idea of help- ing designers model fire
12、s and design tunnel ventilation systems more realistically. However, the model developed relied on the user prescribing the fire heat release rate and did not account for combustion, so the need is still there. In Febru- ary 2000, the Society of Fire Protection Engineers (SFPE) held a meeting on fir
13、e protection research needs (SFPE 2000). The results of a survey conducted by SFPE revealed heat J. Greg Sanchez is principal mechanical engineer with New York City Transit. 02006 ASHRAE. 401 release rate, fire growth, and fully developed fires were ranked as the topics having the highest impact in
14、the fire protection industry. SFPE listed the benefits of studying these three topics as better prediction of fire protection performance, stronger underpinning of fire protection designs, better predictions of the effects of fire, and improved protection of people and property. The approach present
15、ed in this paper applies general combustion fundamentals, available in the general engineer- ing literature, to CFD in order to better resolve our engineering needs. The approach, though developed using one commer- cially available CFD software, can be applied to any other soft- ware. Thus, the appr
16、oach is not limited but open to any knowledgeable engineer who understands the physics of fires and CFD modeling theory. Several software packages are commercially available in the market; however, this paper does not endorse any one in particular. FLASHOVER Flashover is not fully understood by curr
17、ent practitioners, perhaps because its definition is very broad. Kennedy (2004) offers a review on how flashover is used in practice. Therefore, it is important to concur on what flashover may be. In this paper, flashover follows Karlsson and Quintiere?s (2000) defi- nition: flashover is determined
18、by detecting when the upper layer temperature reaches 600C. CURRENT FIRE MODELING APPROACHES A large series of experiments have been conducted to learn about fires in tunnels. Among them are the Memorial Fire test program (MHNFHA 1999) and the EUREKA (1 995) project. Some researchers have been learn
19、ing how to model fires and, in particular, what happens after flashover. Knowl- edge of pre-flashover is very important in order to determine means of egress, while knowledge of post-flashover is very important to determine structural integrity. Models have been created to represent fires using one-
20、 dimensional, two-dimensional, and three-dimensional math- ematical formulations. A one-dimensional model is computa- tionally very quick, but it has many assumptions built in that can be very easily violated, and this would lead to overhnder- predictions depending on the quality ofthe assumptions m
21、ade. Therefore, increasing the dimension of the algorithm should improve the predictions made, One of the most popular two- dimensional computer models is the zone model CFAST (Jones et al. 2004). COMPF-2 (Babrauskas 1979) is another computer model developed to estimate post-flashover condi- tions i
22、n a single compartment. Both of these models rely heavily on empirical formulations to predict the flow in the two-dimensional space, trying to represent a three-dimen- sional space. A full three-dimensional approach involves the use of CFD, also known asjeld models. This is the most accu- rate appr
23、oach because the flow field is solved in three-dimen- sional space. The drawback of increasing the spatial dimension is that time and cost increase exponentially as the number of the dimension increases. Current fire modeling approaches prescribe fires with either constant or time-varying volumetric
24、 heat release rates. However, most of them do not account for fundamental phys- ics present in fire dynamics. Such physics are: pyrolysis mass loss mass availability ignition temperatures for surfaces auto-ignition temperatures for fuel vapors flammability limits radiation optical mass density to es
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