Using thermal analysis experiment and Fire Dynamics Simulator (FDS) to reconstruct an arson fire scene

2012 ◽  
Vol 113 (2) ◽  
pp. 641-648 ◽  
Author(s):  
Jen-Hao Chi
2015 ◽  
Vol 763 ◽  
pp. 134-139 ◽  
Author(s):  
Cherng Shing Lin ◽  
Min Gen Wu ◽  
Sheng Min Tsai

A large number of factories have been sequentially established in Taiwan following the economic take-off several decades ago. However, this growth in number has led to the prevalence of fire hazards. Factory fires typically cause substantial casualties and property losses, and have therefore become a focal point for research. In the present study, the researchers employed the Fire Dynamics Simulator (FDS) software developed by the National Institute of Standards and Technology (NIST) to simulate and evaluate a factory fire scene in Taiwan. The fire continued for approximately 74 h, rendering this outbreak the single longest building fire and rescue in Taiwan. By analyzing relevant data, the researchers established a numerical model of the fire scene to simulate, evaluate, and analyze the influences that temperature, smoke conditions, and smoke layer height parameters had on the fire scene. The findings enabled the researchers to better understand the damage conditions that occur during fire outbreaks. The results of this case study can serve as a reference for designing and improving future fire prevention and safety plans.


Author(s):  
Jan-Michael Cabrera ◽  
Robert Moser ◽  
Ofodike A. Ezekoye

Abstract Fire scene reconstruction and determining the fire evolution (i.e. item-to-item ignition events) using the post-fire compartment is an extremely difficult task because of the time-integrated nature of the observed damages. Bayesian methods are ideal for making inferences amongst hypotheses given observations and are able to naturally incorporate uncertainties. A Bayesian methodology for determining probabilities to items that may have initiated the fire in a compartment from damage signatures is developed. Exercise of this methodology requires uncertainty quantification of these damage signatures. A simple compartment configuration was used to quantify the uncertainty in damage predictions by Fire Dynamics Simulator (FDS), and a compartment evolution program, JT-risk as compared to experimentally derived damage signatures. Surrogate sensors spaced within the compartment use heat flux data collected over the course of the simulations to inform damage models. Experimental repeatability showed up to 4% uncertainty in damage signatures between replicates . Uncertainties for FDS and JT-risk ranged from 12% up to 32% when compared to experimental damages. Separately, the evolution physics of a simple three fuel package problem with surrogate damage sensors were characterized in a compartment using experimental data, FDS, and JT-risk predictions. An simple ignition model was used for each of the fuel packages. The Bayesian methodology was exercised using the damage signatures collected, cycling through each of the three fuel packages, and combined with the previously quantified uncertainties. Only reconstruction using experimental data was able to confidently predict the true hypothesis from the three scenarios.


RSC Advances ◽  
2019 ◽  
Vol 9 (70) ◽  
pp. 41126-41134 ◽  
Author(s):  
Li-Feng Ren ◽  
Qing-Wei Li ◽  
Jun Deng ◽  
Xiao Yang ◽  
Li Ma ◽  
...  

The effect of carbon dioxide and oxygen concentration on thermal behavior of coal oxidation and combustion of coal were investigated using an STA449F3 thermal analysis experiment.


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