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A hybrid stochastic Lagrangian – cellular automata framework for modelling fire propagation in inhomogeneous terrains

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Title: A hybrid stochastic Lagrangian – cellular automata framework for modelling fire propagation in inhomogeneous terrains
Authors: Mastorakos, E
Gkantonas, S
Efstathiou, G
Giusti, A
Item Type: Journal Article
Abstract: A stochastic model motivated by the Lagrangian transported probability density function method for turbulent reacting flows and the cellular automata approach for forest fires was put together to simulate propagation of fires in terrains with inhomogeneous composition. In contrast to the usual cellular automata models for fires where the probability of ignition is prescribed, here the ignition of cells is determined by a random walk that mimics turbulent convection and diffusion of the hot gases and firebrands from upwind and neighbouring fire fronts. Radiation is also included. The model is aimed at speed of computation while approximating the key physics through only a few terrain-related inputs and tunable parameters representing fire intensity, hot gas and ember decay timescales, cell ignition delay and local turbulence. These parameters were calibrated against controlled fire experiments and the model was then used to give reasonable predictions for fires of increasing complexity. The presented framework allows improvements for more accurate representation of the flammable material characteristics, fire-induced flow modifications, and most other phenomena present in fires, hence providing an extendable and simple yet physically-realistic novel modelling approach.
Issue Date: 7-Jun-2023
Date of Acceptance: 19-Jul-2022
URI: http://hdl.handle.net/10044/1/99798
DOI: 10.1016/j.proci.2022.07.240
ISSN: 0082-0784
Publisher: Elsevier
Start Page: 3853
End Page: 3862
Journal / Book Title: Proceedings of the Combustion Institute
Volume: 39
Issue: 3
Copyright Statement: © 2022 The Author(s). Published by Elsevier Inc. on behalf of The Combustion Institute. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Publication Status: Published
Online Publication Date: 2022-09-24
Appears in Collections:Mechanical Engineering
Faculty of Engineering



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