The primary objective of this project was to understand and characterize wildland fire spread at small scales (roughly 1m—1mm) using high fidelity direct and large eddy simulations (direct numerical simulations [DNS] and large eddy simulation [LES], respectively) with reduced chemical kinetic mechanisms calibrated using data from frequency comb laser diagnostics (FCLD). Specific objectives of this project were to (i) Understand and characterize wildland fire spread at scales from roughly 1m to below 1mm using DNS and LES to directly resolve relevant fluid and chemical processes. (ii) Develop and calibrate reduced chemical kinetics mechanisms for the pyrolysis, ignition, and combustion of wildland fuels. (iii) Use frequency comb laser diagnostics to study wildland fire spread at small scales by providing data for the calibration of reduced chemical mechanisms and for simulation validation. (iv) Use insights from the computations and experiments to perform improved simulations of wildland fire spread at landscape scales.
This project consisted of a joint computational and experimental effort focused on two configurations. In the first, pyrolysis, ignition, and burning of solid wood samples were measured and simulated in a mass-loss calorimeter. Different wood types, moisture contents, and radiative fluxes were examined. The resulting experimental data were used to develop and calibrate reduced chemical kinetic models for pyrolysis and gas phase combustion, as well as for validation of the computational simulations. In the second configuration, fire spread was examined in a novel tilting wind tunnel, called the WindCline, for different fuel types, crossflow wind speeds, and slope angles. Experimental measurements of temperature, water mole fraction, flame height, and spread rate for different conditions were used to validate the simulations.
This project was the first to demonstrate the use of adaptive mesh refinement (AMR) for physically accurate and computationally efficient simulations of buoyancy driven flows, pool fires, laboratory-scale biomass combustion, and wildland fire spread. Complex reaction mechanisms for pyrolysis and gas phase combustion were successfully reduced using automated mechanism reduction software, resulting in chemical models that were sufficiently compact for implementation in the AMR simulations. This project was also the first to use FCLD to study evaporation, pyrolysis, ignition, and combustion of solid wildland fuels. Both near-infrared and mid-infrared FCLD were used to calculate time series of temperature and species concentrations during biomass evaporation, pyrolysis, ignition, and combustion for different fuel types and fuel moisture contents. Finally, simulations of fire spread at larger scales were performed using simulations with AMR in both solid and gas phases. Again, this was the first demonstration of AMR for simulations of large-scale fire spread, showing that grid adaptation can be used to significantly reduce computational cost while maintaining physical accuracy.
The combined computational and experimental approach of this project provided unprecedented access to information about chemical species, temperature, and turbulence during the entire pyrolysis, evaporation, ignition, and combustion process, thereby permitting more complete understanding of the physics that must be represented by coarse-scale numerical models of wildland fire spread. This project was also specifically focused on the small-scale behavior of wildland fires and has provided a simulation capability that fills a gap in the current hierarchy of wildland fire computational models. An important outcome of this project was the development of an AMR-based computational capability, which will be of direct benefit for the planning and prediction of prescribed burns. Ultimately, this research has brought together two cutting-edge technologies (AMR and FCLD) for the first time in wildland fire research.