Tuesday, 13 November 2001: 2:30 PM
Studying wildfire behavior using firetec
Current wildfire models range in complexity from simple algebraic models that may be implemented in graphical form or on hand-held calculators to complex formulations that are implemented on large computers. The models of different complexities are appropriate for different applications based on environmental conditions of the modeled fires, the completeness of the available fuels and weather data, the computational resources available, and the time urgency of the results. Many of the more complex models are not currently suitable for faster than real time applications because of their very computationally intensive nature, but their more complete nature allows them to be used to examine some of the more complex wildfire behaviors. FIRETEC is a coupled atmosphere/wildfire behavior model being developed at Los Alamos National Laboratory, and is based on conservation of mass, momentum, species, and energy. FIRETEC is a transport formulation that uses a compressible-gas formulation to couple its physics based wildfire model with the motions of the local atmosphere. We are beginning to use the three-dimensional version of FIRETEC to study the interaction between nonhomogeneities in vegetation, topography, and atmospheric conditions. Examples of the types of physical phenomenon that are being studied are the effects of transient wind conditions, the effects of nonhomogeneous terrain, the effects of non uniform (patchy distributions), and the effects of different vertical structure on fire behavior. In addition we are performing a set of studies on real fires in order to validate or identify problems with the model and we are starting to run FIRETEC on postulated fires in critical areas for risk assessment. Until we reach the point where models such as FIRETEC can be used for operational purposes, we can begin to use them to learn more about the physical processes that current operational models do not adequately represent. By studying these physical processes we can better develop the simple models and determine situations where they are should be used with caution.