Numerical investigation of prediction performance of design fire curves for a tunnel fire
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DOI 10.1007/s12206-020-0838-4
Journal of Mechanical Science and Technology 34 (9) 2020 Original Article DOI 10.1007/s12206-020-0838-4 Keywords: · Design fire curves · Fire dynamics simulator · Large eddy simulation · Mixing controlled fast chemistry · Mixture fraction · Tunnel fire
Correspondence to: Chang Bo Oh [email protected]
Citation: Myilsamy, D., Oh, C. B., Lee, C. Y. (2020). Numerical investigation of prediction performance of design fire curves for a tunnel fire. Journal of Mechanical Science and Technology 34 (9) (2020) 3875~3887. http://doi.org/10.1007/s12206-020-0838-4
Received March 16th, 2020 Revised
May 27th, 2020
Accepted June 18th, 2020 † Recommended by Editor Yong Tae Kang
© The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2020
Numerical investigation of prediction performance of design fire curves for a tunnel fire Dinesh Myilsamy1, Chang Bo Oh1 and Chi Young Lee2 1
2
Department of Safety Engineering, Pukyong National University, Busan 48513, Korea, Department of Fire Protection Engineering, Pukyong National University, Busan 48513, Korea
Abstract The prediction performance of design fire curves is numerically investigated for tunnel fire using the fire dynamics simulator (FDS). A large eddy simulation (LES) was adopted in the simulation of a previous 750 kW tunnel fire experiment. Based on the experimental heat release rate, t2-fire growth, quadratic and exponential design fire curves (DFCs) are mathematically constructed and adopted in the FDS simulation. The predictions of each DFCs are compared against the experimentally measured smoke temperature, smoke travel time, and carbon monoxide (CO) concentration. In addition, the prediction performance of the mixture fraction (MF) and mixing controlled fast chemistry (MCFC) combustion models, is compared. The simulation results of the MF and MCFC models are similar except for the CO concentration features. For the performance of the DFCs, t2-fire growth curve with the MF combustion model is the most effective combination, which demonstrated the most reasonable agreement with the experimental data. 1. Introduction Tunnel transportation is a fast and efficient transportation system, especially in urban and mountainous areas. In addition, tunnel transportation reduces noise pollution and traffic congestion in cities. However, when a tunnel fire accident occurs, it causes catastrophic damage to human life and transportation facilities. Many sever tunnel fire accidents in road tunnels have occurred worldwide, such as those in St. Gotthard (1997), Mont Blanc (1999), Kaprun (2000), Tauern (2002), Trojane (2011), and Gudvanga (2013) tunnels [1]. To understand the potential risks involved in tunnel fire accidents and to enhance public safety, various tunnel fire studies have been performed [2-8]. However, tunnel fire experiments are complex, difficult to reproduce, and expensive. In addition, it is not feasible to perform experiments with many different fire scenarios. Hence, numerical simulations
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