Combustion Simulations with reduced mechanisms using hybrid optimization
Abstract: In order to simulate complex combustion systems, the kinetic mechanisms describing the chemical processes have to be reduced. To minimize the error introduced by the reduction, coefficients of the reaction rates included in the mechanisms can be adjusted in ways so that simulations using the reduced mechanism behave like simulations that use detailed mechanisms. One can then run simulations with different sets of reaction coefficients and compare the result to that of a detailed mechanism thus knowing if the new set of coefficients was better than the old or not. This can be done using an optimization algorithm that in smart ways picks sets of coefficients and uses them in simulations. In this project, simulated annealing and a genetic algorithm is used together to create a hybrid algorithm in order to mitigate each other’s weaknesses to ultimately find better coefficients.
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