2008 ◽  
Vol 13 (5) ◽  
pp. 736-740 ◽  
Author(s):  
Nan Gao ◽  
Wenguo Weng ◽  
Wei Ma ◽  
Shunjiang Ni ◽  
Quanyi Huang ◽  
...  

2014 ◽  
Vol 568-570 ◽  
pp. 1987-1990
Author(s):  
Hong Po Wang ◽  
Hong Zhou

The Drum-Tower District is a historic site in the Inner place of Tianjin which represents the commercial culture,ecdemic culture,exotic culture and civilian culture of Tianjin. The buildings of this region are usually made of wood and other highly combustible materials. Once there be a fire, the influence will be very serious. The study of fire spread model Drum-Tower District is necessary. In the model of fire spread the cellular automaton rules were used. The effects of the different influence coefficients on the evacuation time were investigated, and the typical characteristics of space-time dynamics were analyzed. The numerical simulations show that the model is very good and can be used as a tool to predict fire.


2005 ◽  
Vol 70 (594) ◽  
pp. 1-6 ◽  
Author(s):  
Yoshikazu DEGUCHI ◽  
Mamoru KOHNO ◽  
Makoto TSUJIMOTO ◽  
Tatsuhiro GOTO

2018 ◽  
Vol 76 (5) ◽  
pp. 3602-3614 ◽  
Author(s):  
Chundong Lv ◽  
Jia Wang ◽  
Fanfei Zhang

2012 ◽  
Vol 28 (2) ◽  
pp. 795-810 ◽  
Author(s):  
Geoff Thomas ◽  
David Heron ◽  
Jim Cousins ◽  
Mairéad de Róiste

This paper describes the development of a GIS-based dynamic fire-spread model, with seven distinct modes of fire spread: direct contact, spontaneous ignition of claddings, piloted ignition of claddings, spontaneous ignition through windows, piloted ignition through broken windows, fire spread via non-fire-rated roofs and branding. All except the first two modes include in-built probabilities, but these can be selected individually and given user-defined values. Fire spread modes can be added to the model or altered to suit available building information. Critical details of buildings are obtained from an existing-buildings database, street surveys, or deduced using conditional probabilities from available data. Results show that comparison with actual fires is reasonable. The model could be extended with further development for use as a real time firefighting tool.


2011 ◽  
Vol 4 (1) ◽  
pp. 497-545 ◽  
Author(s):  
J. Mandel ◽  
J. D. Beezley ◽  
A. K. Kochanski

Abstract. We describe the physical model, numerical algorithms, and software structure of WRF-Fire. WRF-Fire consists of a fire-spread model, implemented by the level-set method, coupled with the Weather Research and Forecasting model. In every time step, the fire model inputs the surface wind, which drives the fire, and outputs the heat flux from the fire into the atmosphere, which in turn influences the atmosphere. The level-set method allows submesh representation of the burning region and flexible implementation of various kinds of ignition. WRF-Fire is distributed as a part of WRF and it uses the WRF parallel infrastructure for parallel computing.


2020 ◽  
Vol 29 (3) ◽  
pp. 258 ◽  
Author(s):  
Miguel G. Cruz ◽  
Richard J. Hurley ◽  
Rachel Bessell ◽  
Andrew L. Sullivan

A field-based experimental study was conducted in 50×50m square plots to investigate the behaviour of free-spreading fires in wheat to quantify the effect of crop condition (i.e. harvested, unharvested and harvested and baled) on the propagation rate of fires and their associated flame characteristics, and to evaluate the adequacy of existing operational prediction models used in these fuel types. The dataset of 45 fires ranged from 2.4 to 10.2kmh−1 in their forward rate of fire spread and 3860 and 28000 kWm−1 in fireline intensity. Rate of fire spread and flame heights differed significantly between crop conditions, with the unharvested condition yielding the fastest spreading fires and tallest flames and the baled condition having the slowest moving fires and lowest flames. Rate of fire spread in the three crop conditions corresponded directly with the outputs from the models of Cheney et al. (1998) for grass fires: unharvested wheat → natural grass; harvested wheat (~0.3m tall stubble) → grazed or cut grass; and baled wheat (<0.1m tall stubble) → eaten-out grass. These models produced mean absolute percent errors between 21% and 25% with reduced bias, a result on par with the most accurate published fire spread model evaluations.


2004 ◽  
Vol 176 (2) ◽  
pp. 135-182 ◽  
Author(s):  
G. C. VAZ ◽  
J. C. S. ANDRÉ ◽  
D. X. VIEGAS

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