Presented March 10, 2022- Presentation Slides
“Physics-Based Modeling of Fire Behavior and Smoke Plume Development: How Much is Enough?” by Mr. William Mell (SERDP Project RC19-1132)
Prescribed fires are an essential tool that the Department of Defense (DoD) uses to manage installation lands. This project supported DoD’s goal to manage ecological systems on installations by evaluating and advancing models that can be used to plan prescribed fires. The presentation discussed the comparison of models with different degrees of physical fidelity. The project team compared the modelled predictions of fire behavior, fire-atmosphere interaction, and smoke plume development, as well as the trade-off between the physical fidelity of a model and computational cost. The results of this proof-of-concept study suggest that, depending on domain size and user needs, semi-routine simulations using three-dimensional, time-dependent computational fluid dynamics (CFD)-based fire behavior and smoke plume models are within reach for use as prescribed-burn planning tools. Land management end users with access to high-end desktop computers and cloud computing will be able to utilize these models more readily.
“3D Fuel Characterization for Evaluating Physics-based Fire Behavior, Fire Effects, and Smoke Models on US Department of Defense Military Lands” by Dr. Susan Prichard (SERDP Project RC19-1064)
In the near future, physics-based models will provide near real-time prediction of fire behavior, smoke, and fire effects based on three-dimensional (3D) fuel characterization. However, before these models can be widely used, more research on fuel characterization and mapping methods is needed for 3D model inputs. The project objective was to characterize surface and canopy fuels on pine-dominated sites in the southeastern and western United States and on western grasslands similar to DoD and Department of Energy lands where prescribed fires are used. This presentation covered the development of a library of tools and datasets to develop multi-scale estimates of 3D fuel structure and consumption that can be used in physics-based computational fluid dynamics (CFD) models of fire behavior and smoke production. The project team developed a hierarchical sampling framework to characterize and map fuels in 3D. The hierarchical sampling framework uses a combination of airborne lidar and high-altitude structure-from-motion (SfM) photogrammetry for synoptic mapping of wildland fuels. Low-altitude SfM photogrammetry and terrestrial lidar are used for finer-scale characterization of surface fuels and are calibrated with field-based measures that sample occupied volume and mass within 3D sampling frames.
3D fuel characterization will allow prescribed fire and resource managers to (1) evaluate the effectiveness of fuels and thinning treatments due to changes in surface and canopy fuels and changes in the effect of wind flow on wildland fire behavior; (2) inform the expansion of prescription margins for planning and executing prescribed burning and managed wildfires; and (3) compare spatially-explicit fire radiative energy outputs with resolved fuel consumption and atmospheric interactions to improve models of smoke production and dispersion.
Mr. William (Ruddy) Mell is a combustion engineer with the U.S. Forest Service Pacific Wildland Fire Sciences Lab in Seattle, WA. Mr. Mell has been involved with computer modeling of wildland fires and wildland-urban interface fires for the past 15 years. Prior to entering the field of wildland fire, he worked on modeling turbulent combustion, microgravity combustion, and structure fires at the U.S. National Institute of Standards and Technology (NIST). He currently works closely with experimentalists and other modelers at the U.S. Forest Service, NIST, and other academic institutions. Mr. Mell’s focuses on collaborative efforts with NIST to develop and test a suite of fire and smoke models contained in the Fire Dynamics Simulator. One objective of these models is to provide better tools for planning prescribed fires. He earned a bachelor’s degree in geophysics from the University of Minnesota, Minneapolis and master’s and doctoral degree in Applied Mathematics at the University of Washington, Seattle.
Dr. Susan Prichard is a fire ecologist and has worked as a research scientist at the University of Washington for the past 18 years. Her main research interests focus on the effects of fire, climate change, and other disturbances on forest ecosystems, and fuel treatment options to mitigate fire severity and smoke impacts in dry forests. Having lived through record-setting wildfire seasons, she focuses on applied research questions that inform adaptive management practices in response to climate change. Her methods include innovative approaches to wildland fuel characterization and fire modeling. Dr. Prichard received her bachelor’s degree from The Evergreen State College in Olympia, WA, and her master’s and doctoral degrees in ecosystem science from the University of Washington in Seattle.