Phase Optimized Skeletal Mechanisms in a Stochastic Reactor Model for Engine Simulation

By dividing the combustion process into several phases with phase optimized skeletal mechanisms (POSM), gains in calculation speed were realized with virtually no loss in accuracy.

A skeletal mechanism is a reduced mechanism where only the significant species, determined through a set of parameters (one for each species), remain with respect to a detailed mechanism. The parameter is based on a combination of sensitivity and flow analysis. Within the POSM method machine learning algorithms are used to automatically determine and recognize the major phases. Reduction is achieved by keeping only the significant species with respect to each phase. Each phase has a different mechanism, derived from the original and each is smaller than the original.

This novel approach was implemented into a two-zone zero-dimensional stochastic reactor model (SRM) for an SI-Engine with a 125 species heptane-toluene mechanism and showed that calculation speed was increased by a factor 3 with almost no loss in accuracy.

Further time savings and accuracy improvements from these preliminary results are expected from further reduction of the phase mechanisms