Turbulence and fire-spotting effects into wild-land fire simulators

TL;DR

This paper introduces a mathematical model to incorporate turbulence and fire-spotting effects into wildfire simulators, comparing Lagrangian and Eulerian methods, and demonstrating improved fire behavior simulation with the Lagrangian approach.

Contribution

It adapts a probabilistic formulation for random fire effects to a Lagrangian wildfire simulator and compares its performance with an Eulerian method, highlighting potential operational benefits.

Findings

DEVS-based wildfire model better reproduces complex fire behaviors

The formulation is adaptable from Eulerian to Lagrangian frameworks

Preliminary results suggest improved simulation of fire spread phenomena

Abstract

This paper presents a mathematical approach to model the effects of phenomena with random nature such as turbulence and fire-spotting into the existing wildfire simulators. The formulation proposes that the propagation of the fire-front is the sum of a drifting component (obtained from an existing wildfire simulator without turbulence and fire-spotting) and a random fluctuating component. The modelling of the random effects is embodied in a probability density function accounting for the fluctuations around the fire perimeter which is given by the drifting component. In past, this formulation has been applied to include these random effects into a wildfire simulator based on an Eulerian moving interface method, namely the Level Set Method (LSM), but in this paper the same formulation is adapted for a wildfire simulator based on a Lagrangian front tracking technique, namely the Discrete Event System Specification (DEVS). The main highlight of the present study is the comparison of the performance of a Lagrangian and an Eulerian moving interface method when applied to wild-land fire propagation. Simple idealised numerical experiments are used to investigate the potential applicability of the proposed formulation to DEVS and to compare its behaviour with respect to the LSM. The results show that DEVS based wildfire propagation model qualitatively improves its performance (e.g., reproducing flank and back fire, increase in fire spread due to pre-heating of the fuel by hot air and firebrands, fire propagation across no fuel zones, secondary fire generation, \dots). Though the results presented here are devoid of any validation exercise and provide only a proof of concept, they show a strong inclination towards an intended operational use. The existing LSM or DEVS based operational simulators like WRF-SFIRE and ForeFire respectively can serve as an ideal basis for the same.