Dimensionality Reduction Using a Dominant Dynamic Variable, Self Similarity and Data Tabulation: Application to Hydrocarbon Oxidation

Abstract

A dimensionality reduction method is developed for autonomous dynamical systems exploiting the local (near) self similarity due to the presence of a dominant dynamic variable. The method is coupled with a simple tabulation scheme to take advantage of the computationally more efficient local partial self similarity. The proposed methodology is used to construct reduced kinetics models of hydrocarbon oxidation and is tested for a n-dodecane/air mixture.

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