FIRE MODELLING AS A PREVENTION OF INTERIOR FIRE FATALITIES

Author(s):  
Jana Mullerova ◽  
Maros Krajcir
Keyword(s):  
2001 ◽  
Vol 10 (2) ◽  
pp. 241 ◽  
Author(s):  
Jon B. Marsden-Smedley ◽  
Wendy R. Catchpole

An experimental program was carried out in Tasmanian buttongrass moorlands to develop fire behaviour prediction models for improving fire management. This paper describes the results of the fuel moisture modelling section of this project. A range of previously developed fuel moisture prediction models are examined and three empirical dead fuel moisture prediction models are developed. McArthur’s grassland fuel moisture model gave equally good predictions as a linear regression model using humidity and dew-point temperature. The regression model was preferred as a prediction model as it is inherently more robust. A prediction model based on hazard sticks was found to have strong seasonal effects which need further investigation before hazard sticks can be used operationally.


Fire ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 27
Author(s):  
Maryam Ghodrat ◽  
Farshad Shakeriaski ◽  
David James Nelson ◽  
Albert Simeoni

This work provides a detailed overview of existing investigations into the fire–wind interaction phenomena. Specifically, it considers: the fanning effect of wind, wind direction and slope angle, and the impact of wind on fire modelling, and the relevant analysis (numerical and experimental) techniques are evaluated. Recently, the impact of fire on buildings has been widely analysed. Most studies paid attention to fire damage evaluation of structures as well as structure fire safety engineering, while the disturbance interactions that influence structures have been neglected in prior studies and must be analysed in greater detail. In this review article, evidence regarding the fire–wind interaction is discussed. The effect of a fire transitioning from a wildfire to a wildland–urban interface (WUI) is also investigated, with a focus on the impact of the resulting fire–wind phenomenon on high- and low-rise buildings.


Author(s):  
S Vianna ◽  
K Shaba ◽  
J Pujol ◽  
A Garcia-Sagrado ◽  
L Oliveira

2020 ◽  
Vol 56 (5) ◽  
pp. 1937-1941
Author(s):  
Chin Ding Ang ◽  
Guillermo Rein ◽  
Joaquim Peiro
Keyword(s):  

2019 ◽  
Vol 28 (3) ◽  
pp. 205 ◽  
Author(s):  
Longyan Cai ◽  
Hong S. He ◽  
Yu Liang ◽  
Zhiwei Wu ◽  
Chao Huang

Fire propagation is inevitably affected by fuel-model parameters during wildfire simulations and the uncertainty of the fuel-model parameters makes forecasting accurate fire behaviour very difficult. In this study, three different methods (Morris screening, first-order analysis and the Monte Carlo method) were used to analyse the uncertainty of fuel-model parameters with FARSITE model. The results of the uncertainty analysis showed that only a few fuel-model parameters markedly influenced the uncertainty of the model outputs, and many of the fuel-model parameters had little or no effect. The fire-spread rate is the driving force behind the uncertainty of other fire behaviours. Thus, the highly uncertain fuel-model parameters associated with spread rate should be used cautiously in wildfire simulations. Monte Carlo results indicated that the relationship between model input and output was non-linear and neglecting fuel-model parameter uncertainty of the model would magnify fire behaviours. Additionally, fuel-model parameters have high input uncertainty. Therefore, fuel-model parameters must be calibrated against actual fires. The highly uncertain fuel-model parameters with high spatial-temporal variability consisted of fuel-bed depth, live-shrub loading and 1-h time-lag loading are preferentially chosen as parameters to calibrate several wildfires.


2016 ◽  
Vol 25 (1) ◽  
pp. 1 ◽  
Author(s):  
Roger D. Ottmar ◽  
J. Kevin Hiers ◽  
Bret W. Butler ◽  
Craig B. Clements ◽  
Matthew B. Dickinson ◽  
...  

The lack of independent, quality-assured field data prevents scientists from effectively evaluating and advancing wildland fire models. To rectify this, scientists and technicians convened in the south-eastern United States in 2008, 2011 and 2012 to collect wildland fire data in six integrated core science disciplines defined by the fire modelling community. These were fuels, meteorology, fire behaviour, energy, smoke emissions and fire effects. The campaign is known as the Prescribed Fire Combustion and Atmospheric Dynamics Research Experiment (RxCADRE) and sampled 14 forest and 14 non-forest sample units associated within 6 small replicate (<10 ha) and 10 large operational (between 10 and 1000 ha) prescribed fires. Precampaign planning included identifying hosting agencies receptive to research and the development of study, logistics and safety plans. Data were quality-assured, reduced, analysed and formatted and placed into a globally accessible repository maintained by the US Forest Service Research Data Archive. The success of the RxCADRE project led to the commencement of a follow-on larger multiagency project called the Fire and Smoke Model Evaluation Experiment (FASMEE). This overview summarises the RxCADRE project and nine companion papers that describe the data collection, analysis and important conclusions from the six science disciplines.


2020 ◽  
Author(s):  
Nils Johansson ◽  
Johan Anderson ◽  
Robert McNamee ◽  
Christian Pelo

2014 ◽  
Vol 52 (1) ◽  
pp. 25-50 ◽  
Author(s):  
M. J. Spearpoint ◽  
G. B. Baker

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