Evaluating the sensitivity of surrogate optimization target properties characterizing droplet formation, evaporation, and chemical reactions to biodiesel composition reduction

Abstract

Liquid fuels contain a large number of components. However, it is not computationally feasible to implement the detailed composition into numerical solvers in combustion chamber design. Surrogate mixtures are used to facilitate calculations, which can reproduce the fuel characteristics with fewer components providing reasonable accuracy. Target properties are selected to characterize atomization, evaporation, and chemistry, and the composition is optimized. Even biodiesels, promising alternatives to conventional hydrocarbon fuels, are composed of numerous species. There are dominant components, which can imply the possibility of composition reduction. However, the sensitivity of target properties used for surrogate optimization to composition reduction is seldom discussed in the literature. The motivation of this work is to fill this gap by evaluating representative biodiesel samples with computational models. Fuel volatility shows higher sensitivity to component reduction than properties affecting atomization and chemical reactions. The distillation curve cannot consider the ambient temperature used in further simulations; however, it is decisive in the inclusion of less volatile components since they can extend the droplet lifetime by 60% at temperatures below 600 K. Therefore, the application of the droplet evaporation rate as a target property and its sensitivity to component reduction are analyzed.