Optimization of Fuel-Air Mixing for a Scramjet Combustor Geometry Using CFD and a Genetic Algorithm
Type of DegreeThesis
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A new methodology for the optimization of fuel-air mixing in a scramjet combustor using integrated Genetic Algorithms and Computational Fluid Dynamics is presented. A typical combustor design involving Mach 2 crossflow over a rearward facing step with staged normal injection is considered for study and is optimized using this method. The CFD results are validated against experimental results prior to optimization to allow for grid refinement and high accuracy of results. Quantification of typical combustor performance and design parameters is discussed and adaptation for use with CFD grids is presented. An integrated system of computers and software designed for fast computation times has been created. Correlations between variations in physical geometry and optimization of fuel-air mixing are presented.