Improved Chemical Kinetic Model Reduction in pyMARS for Liquid Propellants

The aerospace industry uses chemical kinetic models when designing propulsion systems to acquire specific details about the rate of chemical reactions, heat release, and combustion stability. However, detailed kinetic models are too large and numerically stiff to be used directly in multidimensional reacting flow simulations. pyMARS is an open-source Python-based software package that uses established methods to accurately and automatically reduce the size of these models for a given tolerance error. Currently, it uses homogeneous autoignition simulations to both sample relevant thermochemical states and gauge the error of candidate reduced models---but this type of simulation has limited relevance to aeropropulsion combustion chambers. Here, we add the additional functionality to use one-dimensional laminar flame simulations to sample relevant state data and measure error (via the laminar flame speed). We show the efficacy of this method by comparing the resulting models reduced by pyMARS using the original autoigniton-only benchmarks with those produced using the new laminar flame speed functionality. Combining laminar flame phenomena with autoignition allows for more-consistent retention of important species and reactions in reduced models for a given error tolerance, that more-accurately calculate laminar flame speeds, compared with using autoignition alone. The updated version of pyMARS is available openly and will allow users to produce better reduced models.