Physics-based, reduced-order gas cloud with radiative transport model for rapid simulation of hyperspectral infrared sensors

Abstract

Peter A. KottkeGeorgia Institute of TechnologyGeorge W. Woodruff School of MechanicalEngineering701 Ferst DriveAtlanta, Georgia 30332-0405E-mail: pk57@mail.gatech.eduAndrei G. FedorovGeorgia Institute of TechnologyGeorge W. Woodruff School of MechanicalEngineering and Parker H. Petit Institute ofBioengineering and Bioscience701 Ferst DriveAtlanta, Georgia 30332-0405Abstract. We have developed a reduced-order, physics-based model ofgas cloud transport and combined it with an approximate formulation ofthe equation of radiative transport to enable efficient prediction of spectralirradiation for simulation of hyperspectral infrared sensors. The resultingcombined model is easily implemented, providing a rapid and flexiblein silico experimentation capability. The gas cloud model is based onthe entrainment hypothesis and predicts cloud trajectories in three-dimensions, with elevation changes occurring primarily due to buoyancyeffects and with spreading and accompanying dilution and cooling occur-ring due to a turbulence dominated growth mechanism. The radiationtransport model is simplified through an approximate treatment of scatter-ing that transforms the governing equation from an integro-differentialequation to an ordinary differential equation. The conjugate model hasbeen combined with a simple sensor model and has been validatedthrough comparison to results from large-scale field tests. The utility ofthe simulations has also been demonstrated through inclusion in a largeralgorithm development and analysis program, the chem/bio algorithmdevelopment kit.