Automatic identification and lumping of high-temperature fuel decomposition pathways for chemical kinetics mechanism reduction

The predictive capabilities of Computational Fluid Dynamics (CFD) for combustion systems rely on a proper description the fuel chemistry. growing interest in accurately capturing behavior multi-component mixtures creates additional challenges developing reduced-order chemical kinetics mechanisms small enough to be used CFD. Among suite chemistry reduction approaches available, lumping techniques appear especially suited handle complex nature In particular, published literature provides very strong evidence that non-rate-limiting pathways, and more specifically, high-temperature decomposition reactions, is powerful avenue mechanism reduction. this work, we present novel algorithm identify lump high temperature reactions from detailed kinetic mechanisms. strategy fully automatic, relies exclusively information available mechanism. performance technique assessed both single-component fuel, n-dodecane, its mixture with iso-octane. Results show replacing sub-mechanism by number involving single equivalent component introduces limited changes prediction laminar flame speeds, ignition delay curves, species profiles. This establishes clear potential proposed become valuable addition existing multi-stage software.