Predicting the Combustion Behaviour of Tailorable Advanced Biofuel Blends Using Automatically Generated Mechanisms

Emerging processes such as biomass alcoholysis have the potential to provide tailorable, advanced biofuels to replace conventional fossil fuels. To model the combustion characteristics of the resultant complex blends, automatic mechanism generation (AMG) techniques are applied to produce detailed ethyl (ethyl levulinate, diethyl ether, ethanol) and butyl (n-butyl levulinate, di-n-butyl ether, n-butanol) kinetic mechanisms. The predictive capabilities of these mechanisms are evaluated, showing a high degree of accuracy when compared to ignition delay time (IDT) and speciation measurements, at thermodynamic conditions of relevance to engine technologies.