Optimization of the Syngas Combustion Chemistry Model

Practically, an accurate combustion chemistry model is of great importance in engine simulations when it is combined with the computational fluid dynamics computations. Syngas is used as one of the fuel options in internal combustion engines. In the current work, we optimize a combustion chemistry model of syngas using machine learning algorithms. Result shows that the optimized model can achieve better prediction accuracy than the unoptimized model.