Development of a Reduced Biodiesel Surrogate Fuel Model for Multi-Dimensional Computational Fluid Dynamic Simulations

Abstract

This work reports the development of a reduced biodiesel surrogate fuel model for multi-dimensional Computational Fluid Dynamic simulations. The model is derived using an integrated kinetic mechanism reduction scheme and the final chemistry comprises only 83 species. The model is well validated in zero-dimensional chemical kinetic calculations under a wide range of auto-ignition and jet-stirred reactor conditions. The fidelity of the model is also further assessed in two-dimensional simulations of a constant-volume combustion vessel with respect to the experimental results of soy-methyl ester combustion. The results obtained reveal that ignition delay, lift-off lengths and soot volume fractions are reasonably well replicated by the reduced model. Furthermore, the compositions of the reduced model are varied according to the saturation/unsaturation levels of various biodiesel feed-stocks, such as palm-methyl ester and sunflower-methyl ester. In this work, it is demonstrated that the reduced model can potentially be used as a universal surrogate fuel model to predict the reactivity of biodiesel feed-stocks with low degree of saturation (≤30%) in both kinetic and fuel spray simulations.