Jensen, Sally; Lignell, David (Brigham Young University)
Faculty Advisor: Lignell, David (Ira A. Fulton College of Engineering, Chemical Engineering)
Radiative heat transfer is central to many chemical engineering processes. Turbulent combustion accounts for 80% of the world's energy. Understanding radiative heat transfer is important for efficient design, regulating pollutant emissions, and doing hazard analyses of these processes. Radiation depends on temperature as well as local composition fields. It is important for combustion because it affects heat transfer to surrounding environments. This in turn impacts fire spread in wild fires as well as heat transfer in power plant boilers and other such applications. Radiation also directly affects the temperature field. The temperature field in turn feeds back to the radiation and impacts the formation of pollutants, such as soot, NOx and other species. Modeling is difficult because computing the absorption coefficient depends on the spectral properties of molecules. Computing these requires millions of spectral bands, which is too expensive to compute for normal applications. A common method that is currently used to predict radiation is the Weighted-sum-of-gray-gases model. Doctors Solovjov and Webb developed a new method called the Rank Correlated Integration of the Spectral Line Weighted-sum-of-gray-gases (rcSLW) model. It is a complex model that is difficult to implement, but it is accurate. It has been implemented in python and in C++. The model has been provided on github to allow for easy access by the community. We will present an overview of the rcSLW model and code interface as well as show selected results applied to systems of interest with respect to combustion.