Reduction of a methane pyrolysis chemical kinetic model using a skeleton reduction and genetic algorithm

Many chemical industrial processes release methane as a byproduct, which is usually burned for energy generation. However, if carbon neutrality is to be achieved, methane cannot be released to the atmosphere or burned for energy generation. Plasma pyrolysis has been proposed as a means to convert methane into higher-value hydrocarbons. To optimize and scale-up reactors for this purpose, Computational Fluid Dynamics (CFD) studies are needed. These studies will require reduced order models for thermal reactions. However, there is no consensus on the simplified chemical description of methane conversion, partly since studies on this topic focus on the conditions relevant to specific plasma sources. This work aims at analyzing the dominant reactions of a methane chemical model and using this information to create a reduced model for CFD studies. The analysis is based on a skeletal reduction technique which allows the selection of the important reaction pathways thus creating a skeletal model. The skeletal model is then optimized using a genetic algorithm, generating an optimized model for CFD. Two methane conversion regimes have been identified with radicals playing a major role in the conversion process. The genetic algorithm is shown to consistently provide a reasonable reproduction of the reference model for several test conditions.