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Multifidelity prediction in wildfire spread simulation: Modeling, uncertainty quantification and sensitivity analysis

Author
Miguel , M.; Jofre, L.; Torres, R.
Type of activity
Journal article
Journal
Environmental modelling & software
Date of publication
2021-07-01
Volume
141
First page
105050:1
Last page
105050:11
DOI
10.1016/j.envsoft.2021.105050
Repository
http://hdl.handle.net/2117/347113 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S1364815221000931 Open in new window
Abstract
Wildfire behavior predictions typically suffer from significant uncertainty. However, wildfire modeling uncertainties remain largely unquantified in the literature, mainly due to computing constraints. New multifidelity techniques provide a promising opportunity to overcome these limitations. Therefore, this paper explores the applicability of multifidelity approaches to wildland fire spread prediction problems. Using a canonical simulation scenario, we assessed the performance of control variat...
Citation
Miguel, M.; Jofre, L.; Torres, R. Multifidelity prediction in wildfire spread simulation: Modeling, uncertainty quantification and sensitivity analysis. "Environmental modelling & software", 1 Juliol 2021, vol. 141, p. 105050:1-105050:11.
Keywords
FDS, Forest fire, Multifidelity Monte Carlo, Predictive science & engineering, Sensitivity analysis, Uncertainty quantification
Group of research
GReCEF- Grup de Recerca en Ciència i Enginyeria de Fluids

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