QUIC-fire: A fast-running simulation tool for prescribed fire planning

Linn, Rodman Ray; Goodrick, Scott; Brambilla, Sara; Brown, Michael John; Middleton, Richard Stephen; O'Brien, Joseph J.; Hiers, John Kevin

doi:10.1016/j.envsoft.2019.104616

Title: QUIC-fire: A fast-running simulation tool for prescribed fire planning

Journal Article · 27 December 2019 · Environmental Modelling and Software

DOI: https://doi.org/10.1016/j.envsoft.2019.104616 · OSTI ID:1581577

^[1]; Goodrick, Scott ^[2];

^[1];

^[1]; O'Brien, Joseph J. ^[2]; Hiers, John Kevin ^[3]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
USDA Forest Service Center for Forest Disturbance Science, Athens, GA (United States)
Tall Timbers Research Station, Tallahassee, FL (United States)

Coupled fire-atmospheric modeling tools are increasingly used to understand the complex and dynamic behavior of wildland fires. Multiple research tools linking combustion to fluid flow use Navier-Stokes numerical solutions coupled to a thermodynamic model to understand fire-atmospheric feedbacks, but these computational fluid dynamics approaches require high-performance computing resources. We present a new simulation tool called QUIC-Fire to rapidly solve these feedbacks by coupling the mature 3-D rapid wind solver QUIC-URB to a physics-based cellular automata fire spread model Fire-CA. QUIC-Fire uses 3-D fuels inputs similar to the CFD model FIRETEC, allowing this tool to simulate effects of fuel structure on local winds and fire behavior. Results comparing fire behavior metrics to the computational fluid dynamic model FIRETEC show strong agreement. As a result, QUIC-Fire is the first tool intended to provide an opportunity for prescribed fire planners to compare, evaluate and design burn plans, including complex ignition patterns and coupled fire atmospheric feedbacks.

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Research Organization:: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: LDRD; USDOE

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 1581577

Report Number(s):: LA-UR--19-27513

Journal Information:: Environmental Modelling and Software, Journal Name: Environmental Modelling and Software Journal Issue: C Vol. 125; ISSN 1364-8152

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Prescribed Fire Optimization. In Data Science & Engineering Master of Advanced Study (DSE MAS) Capstone Projects Breslow, Jonah F.; Courtney, Sam C.; Ho, Lam UC San Diego Library Digital Collections https://doi.org/10.6075/j0833s7r	dataset	January 2022

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