While a large number of wildland fires are burning through West Texas and threatening the safety of life and property of Texans, the fire research group at The University of Texas at Austin is actively working with physics-based computer models and laboratory-scale fire tests to characterize the fuel properties and flame spread characteristics of grassland fuels.

Computer model of grassland fire simulation

At UT Austin, we have been performing small-scale, controlled experiments in our burn structure to determine ignition times and burning rates for grassland fuels as well as intermediate-scale, controlled experiments to determine the fuel and combustion properties of grass fuels, the effects of external wind on ember production, and the heat release rates of grass bunches.

Controlled grass fire test in the UT Austin burn structure

We can utilize the results of the small- and intermediate-scale experiments in full-scale computer simulations of grassland fires using modeling tools such as Wildland-urban interface Fire Dynamics Simulator (WFDS).

Using the results and methods from these controlled experiments along with the help of the wildland fire community, we plan to develop a framework to determine fuel properties of wildland fuels, predict the physics and fire dynamics behavior of wildland fires, and achieve safer conditions for people and property faced with the threat of wildland fire situations.

Attached are my PDF slides on the topic of “Inverse fire modeling for heat release rate characterization“, which was presented at the 7th US National Combustion Meeting in Atlanta, GA on March 21, 2011.

The abstract is as follows:

A ubiquitous source of uncertainty in fire modeling is the proper heat release rate for the fuel packages of interest. An inverse heat release rate (HRR) calculation method is presented to determine a HRR that satisfies measured temperature data. The methodology is developed by using synthetic temperature data using the Consolidated Model of Fire and Smoke Transport (CFAST) zone model to produce hot gas layer temperatures in a single compartment. The inverse HRR method runs at super-real-time speeds while calculating an inverse HRR solution that can reasonably well match the original HRR curve. Examples of the inverse HRR method are demonstrated by using a multiple step HRR case, experimental data with a constant HRR, and complex HRR curves. In principle, the methodology can be applied using any reasonably accurate fire model to invert for the HRR.

The slides can be downloaded here: Overholt_Combustion_2011

I’ve posted a new web calculator tool to calculate flame heights and plume centerline temperatures (above the flame height). The calculator is based on the correlations by Heskestad and McCaffrey, and is available here:

http://www.koverholt.com/flame-height-and-plume-centerline-temperature-calculator/

Please let me know if you find any bugs, would like to give feedback on this tool, or have a request for another web calculator!