Abstract
Computational simulations have the potential to provide low-cost, low-risk insights into wildland fire structure and dynamics. Simulation accuracy is limited, however, by the difficulty of modeling physical processes that span a wide range of spatial scales. These processes include heat transfer via radiation and turbulent advection, as well as both solid- and gas-phase chemistry. In the present study, we perform large eddy simulation (LES) with adaptive mesh refinement to model the multi-phase pyrolysis and combustion of dry Douglas fir, where temperature-based lookup tables corresponding to a multi-step pyrolysis mechanism are used to represent the composition of gas-phase pyrolysis products. Gas-phase and surface temperatures, mass loss, and water vapor mole fraction from the LES are shown to compare favorably with experimental measurements of a radiatively heated Douglas fir fuel sample undergoing pyrolysis and combustion beneath a cone calorimeter. Using frequency comb laser diagnostics, optical and infrared cameras, and a load cell, the experiments provide simultaneous in situ, time-resolved measurements of chemical composition, temperature, and mass loss. The present study thus combines cutting edge computational and experimental techniques with multi-step chemical pyrolysis modeling to provide a validated computational tool for the prediction of solid fuel pyrolysis and combustion relevant to wildland fires.
Highlights
It is anticipated that, over the coming decades, climate change will contribute to increased wildland fire activity, in the Western U.S (Westerling et al, 2006; Barbero et al, 2015; Westerling, 2016)
We use large eddy simulations (LES) with adaptive mesh refinement (AMR) in OpenFOAM to simulate the solid wood combustion experiment performed by Makowiecki et al (2020a)
The fireDyMFoam solver retains the physical modeling present in fireFoam, but incorporates AMR and dynamic rebalancing of computational processors to enable computationally efficient, yet high-resolution, simulations of fire spread and suppression. This solver has been described in more detail by Lapointe et al (2020, 2021), where the number of cpu-hours required for AMR simulations was reduced by roughly a factor of five compared to equivalently resolved static mesh simulations, and is used here to perform three-dimensional LES of solid fuel pyrolysis and combustion in coupled gas- and solid-phase regions
Summary
Over the coming decades, climate change will contribute to increased wildland fire activity, in the Western U.S (Westerling et al, 2006; Barbero et al, 2015; Westerling, 2016). We use large eddy simulations (LES) with adaptive mesh refinement (AMR) in OpenFOAM to simulate the solid wood combustion experiment performed by Makowiecki et al (2020a) In this experiment, simultaneous in situ measurements of mass loss, heat flux, optical imaging, surface temperature, gas-phase temperature, and water vapor concentration were made for a fuel sample under a cone calorimeter. The use of AMR has the potential to enable computationally tractable simulations that capture large- and small-scale terrain, as well as detailed fuel features Simulations that include such physically relevant details while incorporating physicsbased modeling could serve as the basis for new subgrid-scale models for existing landscape-scale fire spread modeling efforts. Conclusions and directions for future research are provided at the end
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