The aim of this short review is to present the progress made in wildland fire modelling during the last 50 years and the intellectual track followed by wildland fires models, from fully empirical models in the 60s, to semi-empirical ones in the 70s, to fully physical models at the end of the 90s. During the last period, the large diffusion of HPC methods substantially contributed to the development of multiphase formulations applied to wildland fire modelling. Many studies have particularly focused on the effects of various parameters (vegetation, topography, atmosphere) affecting the behaviour of a fire front propagating through a forest fuel layer.
Revised:
Accepted:
Online First:
Published online:
Dominique Morvan 1; Gilbert Accary 2; Sofiane Meradji 3; Nicolas Frangieh 4
@article{CRMECA_2022__350_S1_107_0, author = {Dominique Morvan and Gilbert Accary and Sofiane Meradji and Nicolas Frangieh}, title = {Fifty years of progress in wildland fire modelling: from empirical to fully physical {CFD} models}, journal = {Comptes Rendus. M\'ecanique}, pages = {107--115}, publisher = {Acad\'emie des sciences, Paris}, volume = {350}, number = {S1}, year = {2022}, doi = {10.5802/crmeca.133}, language = {en}, }
TY - JOUR AU - Dominique Morvan AU - Gilbert Accary AU - Sofiane Meradji AU - Nicolas Frangieh TI - Fifty years of progress in wildland fire modelling: from empirical to fully physical CFD models JO - Comptes Rendus. Mécanique PY - 2022 SP - 107 EP - 115 VL - 350 IS - S1 PB - Académie des sciences, Paris DO - 10.5802/crmeca.133 LA - en ID - CRMECA_2022__350_S1_107_0 ER -
%0 Journal Article %A Dominique Morvan %A Gilbert Accary %A Sofiane Meradji %A Nicolas Frangieh %T Fifty years of progress in wildland fire modelling: from empirical to fully physical CFD models %J Comptes Rendus. Mécanique %D 2022 %P 107-115 %V 350 %N S1 %I Académie des sciences, Paris %R 10.5802/crmeca.133 %G en %F CRMECA_2022__350_S1_107_0
Dominique Morvan; Gilbert Accary; Sofiane Meradji; Nicolas Frangieh. Fifty years of progress in wildland fire modelling: from empirical to fully physical CFD models. Comptes Rendus. Mécanique, More than a half century of Computational Fluid Dynamics, Volume 350 (2022) no. S1, pp. 107-115. doi : 10.5802/crmeca.133. https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.5802/crmeca.133/
[1] Wildland surface fire spread modelling 1990–2007. 1. Physical and quasi-physical models, Int. J. Wildland Fire, Volume 18 (2009), pp. 349-368 | DOI
[2] Wildland surface fire spread modelling 1990–2007. 2. Empirical and quasi-empirical models, Int. J. Wildland Fire, Volume 18 (2009), pp. 369-386 | DOI
[3] Wildland surface fire spread modelling 1990–2007. 3. Simulation and mathematical analogue models, Int. J. Wildland Fire, Volume 18 (2009), pp. 387-403 | DOI
[4] Physical phenomena and length scales governing the behaviour of wildfires: a case for physical modelling, Fire Technol., Volume 47 (2011), pp. 437-460 | DOI
[5] Weather and Grassland Fire Behaviour, Forest Research Institute, Forestry and Timber Bureau, ACT, Australia, 1966
[6] A generic, empirical-based model for predicting rate of fire spread in shrublands, Int. J. Wildland Fire, Volume 24 (2015) no. 4, pp. 443-460 | DOI
[7] Urban and wildland fire phenomenology, Progr. Energy Combust. Sci., Volume 8 (1982) no. 4, pp. 317-354 | DOI
[8] Wildfires modelling: short overview, challenges and perspectives, J. Combust. Soc. Jpn., Volume 61 (2019) no. 196, pp. 120-125
[9] Prescribed fire: science: the case for a refined research agenda, Fire Ecol., Volume 16 (2020) no. 1, pp. 1-15 | DOI
[10] Analysis of fire spread in light forest fuels, J. Agric. Res., Volume 72 (1946) no. 3, pp. 93-121
[11] Fire in the forest, Fire Res. Abstr. Rev., Volume 5 (1964), pp. 163-178
[12] Influence of moisture and wind upon the characteristics of free-burning fires, Symp. Int. Combust., Volume 10 (1965) no. 1, pp. 1009-1019 | DOI
[13] Fire spread through porous fuels from the conservation energy, Combust. Flame, Volume 16 (1971), pp. 9-16 | DOI
[14] A mathematical model for predicting fire spread in wildland fuels (1972) no. Research paper INT6115 (Technical report)
[15] FARSITE: fire area simulator, model development and evaluation, 2004 (Research Paper RMRS-RP-4 Revised. Ogden, UT: US Department of Agriculture, Forest Service, Rocky Mountain Research Station)
[16] Role of buoyant flame dynamics in wildfire spread, Proc. Natl. Acad. Sci. USA, Volume 112 (2015) no. 32, pp. 9833-9838 | DOI
[17] The potential and promise of physics-based wildfire simulation, Env. Sci. Policy, Volume 3 (2000), pp. 161-172 | DOI
[18] A coupled atmosphere-fire model: convective feedback on fire-line dynamics, J. Appl. Meteorol. Clim., Volume 35 (1996) no. 6, pp. 875-901 | DOI
[19] Simulation of coupled fire/atmosphere interaction with the MesoNH-ForeFire models, J. Combust., Volume 2011 (2011), 540390
[20] Coupled atmosphere-wildland fire modeling with WRF-Fire version 3.3, Geosci. Model Dev., Volume 4 (2011), pp. 591-610
[21] A physical model for wildland fires, Combust. Flame, Volume 156 (2009) no. 12, pp. 2217-2230 | DOI
[22] A convective–radiative propagation model for wildland fires, Int. J. Wildland Fires, Volume 29 (2020) no. 8, pp. 723-738 | DOI
[23] Multiscale simulation of a prescribed fire event in the New Jersey Pine Barrens using ARPS-CANOPY, J. Appl. Meteorol. Clim., Volume 53 (2014) no. 4, pp. 793-812 | DOI
[24] The influence of fuel, weather and fire shape variables on fire spread in grasslands, Int. J. Wildland Fire, Volume 3 (1993), pp. 31-44 | DOI
[25] A transport model for the prediction of wildfire behaviour, Ph. D. Thesis, University of New Mexico LANL (1997) | DOI
[26] Multiphase formulation applied to the modeling of fire spread through a forest fuel bed, Proc. Combust. Inst., Volume 28 (2000) no. 2, pp. 2803-2809 | DOI
[27] A physics-based approach to modelling grassland fires, Int. J. Wildland Fire, Volume 16 (2007) no. 1, pp. 1-22 | DOI
[28] Experimental study and large eddy simulation of effect of terrain slope on marginal burning in shrub fuel beds, Proc. Combust. Inst., Volume 31 (2007) no. 2, pp. 2547-2555 | DOI
[29] Large-eddy simulation of turbulent flow above and within a forest, Bound. Layer Meteorol., Volume 61 (1992), pp. 47-64 | DOI
[30] Turbulence in plant canopies, Annu. Rev. Fluid Mech., Volume 32 (2000), pp. 19-71 | DOI | Zbl
[31] Mathematical Modelling of Forest Fires and New Methods of Fighting Them (F. Albini, ed.), Publishing House of the Tomsk State University, Tomsk, Russia, 1997
[32] Wildfire behaviour study in a Mediterranean pine stand using a physically based model, Combust. Sci. Technol., Volume 180 (2007) no. 2, pp. 230-248 | DOI
[33] Numerical study of the behaviour of a surface fire propagating through a fuel break built in a Mediterranean shrub layer, Fire Saf. J., Volume 71 (2015), pp. 34-48 | DOI
[34] Wildfires front dynamics: 3D structures and intensity at small and large scales, Combust. Flame, Volume 211 (2020), pp. 54-67 | DOI
[35] Numerical simulation and experiments of burning douglas fir trees, Combust. Flame, Volume 156 (2009), pp. 2023-2041 | DOI
[36] Wildland fires behaviour: wind effect versus Byram’s convective number and consequences upon the regime of propagation, Int. J. Wildland Fire, Volume 27 (2018) no. 9, pp. 636-641 | DOI
[37] Validation of wildfire spread models, Encyclopedia of Wildfires and Wildland-Urban Interface (WUI) Fires (S. Manzello, ed.), Springer, Cham, 2019 | DOI
[38] Wind effects, unsteady behaviours and regimes of propagation of surface fires in open field, Combust. Sci. Technol., Volume 186 (2014) no. 7, pp. 869-888 | DOI
[39] Using periodic line fires to gain a new perspective on multi-dimensional aspects of forward fire spread, Agric. For. Meteorol., Volume 157 (2012), pp. 60-76 | DOI
Cited by Sources:
Comments - Policy