Community analysis of bifurcation maps of diluted hydrogen combustion in WSFRs

This article focuses on the development of an automatic procedure for the inspection of the very complex kinetic mechanisms required to predict accurately the behavior of new generation fuels. By coupling the bifurcation analysis, which identifies the different regimes occurring with a change of the parameters, with algorithms typical of Artificial Intelligence, specifically the Community Analysis, that identify within a large set of individuals (the chemical species) common behavior patterns, we proposed a novel mechanism analysis method that are capable of automatically extract meaningful information for the identification of the key species responsible for the dynamical behavior from the solution maps of a combustion system. Application in a diluted hydrogen combustion system reveal that the recognition of state change are effective based on the heat release rate and the entropy production rate indexes.