An integrated dynamic adaptive chemistry and hybrid multi-time scale method for combustion modeling with detailed kinetic mechanisms

An integrated dynamic adaptive chemistry and hybrid multi-timescale (HMTS-DAC) method is developed based on the path flux analysis (PFA) model reduction and the hybrid multi-timescale (HMTS) algorithm to increase substantially the computational efficiency of combustion modeling with large, detailed kinetic mechanisms. The HMTS-DAC method is applied to model the ignition and unsteady flame propagation process of n-decane and n-heptane/air mixtures and compared with the implicit ODE solver with and without the dynamic adaptive chemistry. The results show that the method can accurately reproduce the species time histories and ignition delay times. Compared to the implicit ODE solver without a dynamic adaptive chemistry, HMTS-DAC demonstrates more than one-order increase of the computational efficiency. In addition, the probability graph of dynamic adaptive chemistry size for n-decane is generated. The effects of the mechanism size and the criteria of model reduction in path flux analysis are investigated. The results show that the computational efficiency of HMTS-DAC increases with the increase of chemical mechanism size. This scheme is shown to be rigorous and can be used for direct numerical simulations and large eddy simulations with detailed chemical mechanisms to improve the computational efficiency.