Modeling and simulation of a turbulent jet diffusion flame of a biodiesel surrogate composed of MD, n-Hept, MC and EtOH

Abstract

The more properties of biodiesel one wishes to represent, the more complex the surrogate mixture becomes. Often the aim is to represent the H/C and O/C ratios and molecular weight using a small number of pure components. In this article, a turbulent jet diffusion flame of a biodiesel surrogate, composed of 50% Methyl Decanoate, 40% n-heptane, 9% methyl crotonate and 1% ethanol is modeled and simulated. The strategy used is to apply the Directed Relation Graph technique for a first reduction, and Layerless Neural Network to define the main chain and obtain a skeletal mechanism. The results obtained for temperature and mass fractions of CO2, CO and H2O agree reasonably with literature data for a mechanism of 147 reactions and 45 species. The small number of species facilitates the simulation of the coupling between turbulence and chemical kinetics, a desirable feature of reduced mechanisms.