Optimization of Kinetic Mechanism for Methane Combustion Based on Machine Learning
In this work,the experimental data of ignition delay time(T=1084-2175 K,p=7.3×104-2.4×106 Pa,φ=0.2-2.0)and laminar flame speed(T=293-600 K,p=5.1x104-1.1×106 Pa,φ=0.4-2.0)were taken as the optimization objectives based on the machine-learning model constructed by radial basis function interpolation method,and pre-exponential factors and activation energies of CH4 combustion mechanism were optimized,and a CH4 combustion mechanism that can be used in a wide range of working conditions was obtained.Compared with the Ori-CH4 mechanism,the mean error of the Opt-CH4 mechanism is reduced by 57.46％in the ignition delay times and 21.55％in the laminar flame speeds.The Opt-CH4 mechanism was used to predict the ignition delay times,laminar flame speeds and the variation tendency of species concentration in jet stirred reactor.The Opt-CH4 mechanism showed superior prediction accuracy.Under the conditions of T=1491.5 K,p=1.0×105 Pa,4.988％CH4\19.953％O2\75.059％N2(volume fraction),the difference of sensitivity of CH3+O2⇌C H2O+O H and CH2O+O2⇌H1CO+HO2 in each mechanism is the main reason for the difference of prediction accuracy of CH4 mechanism before and after optimization.Therefore,the machine learning method has a broad application prospect in the optimization of fuel combustion reaction kinetics mechanism parameters.
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