Supervision: Jean-Louis Consalvi1, Dominique Morvan1, Gilbert Accari3 & Pierre Boivin2
1 Aix-Marseille Université, IUSTI/UMR CNRS 7343, 5 rue E. Fermi, 13453 Marseille
Cedex 13, France
2 Aix Marseille Univ, CNRS, IUSTI, Marseille, France
3 Lebanese American University (LAU), P.O. Box 36, Byblos, Lebanon
Description of the Post Doc
This research project will be funded by the “Institute for Mechanical Engineering” of Aix-Marseille University. Once selected by the reaserch team, the project and the candidate will be evaluated in a sigle round in November, 2025 for a final decision in December, 2025. The Post Doc will last up to 24 months (12 months renewable once). He/she will benefit from an additional support budget of 5k euros/year (for symposium participation, international collaboration missions, small equipment, etc.).
This research project investigates firebrand spotting, a critical mechanism for fire spread in both wildland and wildland-urban interface (WUI) fires. Firebrands, which are flaming or glowing embers, are generated by burning vegetation or structures. These embers are then lifted by fire plumes and carried downwind, where they can ignite new fires or structures far from the main flame front [1]. Spotting significantly influences fire spread patterns because it acts over much longer distances than heat transfer mechanisms from flames to unburnt vegetation. In addition, it is estimated that more than half of the homes destroyed in WUI fires are due to firebrands [2].
The complex problem of spot wildfires can be broken down into three individual processes:
1. Firebrand generation and thermochemical state: How firebrands are produced and their initial chemical and thermal properties [3].
2. Transport and thermochemical evolution during flight [4].
3. Ignition upon landing: the initiation of smoldering or flaming combustion in a receptive fuel bed after the firebrand lands [1].
Stochastic models have been developed to model firebrand spotting [5, 6, 7]. These models are particularly well-suited for integration into operational fire spread models, providing real-time capabilities that are highly valuable for operational use and decision-making in fire management [7]. The stochastic spotting models rely on model parameters that are difficult to estimate and strongly depend on the weather (wind speed, ambient temperature, relative humidity) and the vegetation (type, moisture content).
This project research aims to combine CFD modeling of the spotting process with statistical learning methods to explore how the stochastic model parameters evolve with the most sensitive input data. The CFD simulations of the spotting process will be performed with FireStar3D, a fully physical, three-dimensional wildfire simulation model, co-developed at M2P2, the Lebanese American University and Toulon University. [8]. A particular fundamental focus of this project will be on developing ignition models for fuel beds by firebrands. This aspect is crucial as it represents the least understood of the three processes previously described in firebrand spotting.
Candidate profile
The desired candidate must hold a PhD related to combustion, fire research, and numerical simulation. The candidate will work in a research laboratory environment and will have to demonstrate autonomy, pragmatism, and a proactive approach.
• Contact and candidature: Jean-Louis Consalvi (jean-louis.consalvi@univ-amu.fr).
References
[1] A. C. Fernandez-Pello, Wildland fire spot ignition by sparks and firebrands, Fire Safety J. 91 (2017) 2–10.
[2] S. E. Caton, R. S. P. Hakes, D. J. Gorhan, A. Zhou, M. J. Gollner, Review of pathways for building fire spread in the wildland urban interface part i: exposure conditions, Fire Technol. 53 (2017) 429–473.
[3] S. L. Manzello, S. Suzuki, M. J. Gollner, A. C. Fernandez-Pello, Role of firebrand combustion in large outdoor fire spread, Prog. Ener. Combust. SCi. 76 (2020) 100801.
[4] N. Sardoy, J. L. Consalvi, B. Porterie, A. C. Fernandez-Pello, Modeling transport and combustion of firebrands from burning trees, Combust. Flame 150 (2007) 151–169.
[5] B. Porterie, N. Zekri, J. P. Clerc, J. C. Loraud, Modeling forest fire spread and spotting process with small world networks, Combust. Flame 149 (2007) 63–78.
[6] E. Mastorakos, S. Gkantonas, G. Efstathiou, A. G. b, A hybrid stochastic lagrangian – cellular automata framework for modelling fire propagation in inhomogeneous terrains, Proc. Combust. Inst. 39 (2023) 3853–3862.
[7] G. Efstathiou, S. Gkantonas, A. Giusti, E. Mastorakos, C. M. Foale, R. F. c, Simulation of the december 2021 marshall fire with a hybrid stochastic lagrangian-cellular automata model, Fire Safety J. 138 (2023) 103795.
[8] N. Frangieh, G. Accary, D. Morvan, S. Meradji, O. Bessonov,Wildfires front dynamics: 3d structures and intensity at small and large scales, Combust. Flame 211 (2020) 54–67.
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Bronwyn Forrest is a 3rd year PhD student at the University of Waterloo, conducting multi-disciplinary research investigating human physiological response to fire exposure. Bronwyn graduated in 2017 with a BSc. Honours Kinesiology and in 2020 with a MASc. Mechanical & Mechatronics Engineering (Heat Release Rate in Ventilation-Limited Furniture Fires) before merging her two degrees in her PhD research. As a senior graduate student in the Fire Research Group, Bronwyn spear-heads large-scale fire experiments, mentors junior graduate and undergraduate students, and has recently set-up a new ‘human exposure lab’ at the Fire Research Facility where she leads new research in that area. Since her induction into the world of fire science, Bronwyn has grown more and more passionate about the multi-faceted nature of emerging fire safety challenges. Through innovative research, she hopes to make meaningful contributions that help shape changes to fire safety over the course of her career.
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