Author: Shuliang ZhangPublisher:
ISBN:
Category : Biodiesel fuels
Languages : en
Pages : 97
Book Description
The primary objective of this research is to characterize fuel combustion in reactive flow simulations using advanced kinetic modeling and mechanism reduction tools. Since incorporating detailed chemical kinetic model in the realistic reactive flow simulations is a computationally challenging task due to the large size of detailed kinetic mechanism, it is of great interest to develop approaches for simplifying the kinetic models and reducing computational costs in reactive flow simulations. In this dissertation, we first extend the previously developed on-the-fly reduction approach to the characterization of complex biodiesel combustion using detailed biodiesel surrogate mechanism. Major combustion characteristics such as ignition, emission, as well as engine performance for biodiesel compared with conventional fossil fuels are studied. Although the incorporation of detailed biodiesel combustion mechanism in complex reactive flow simulation is enabled, the simulation is still highly time-consuming. To further alleviate the computational intensity, a hybrid reduction scheme coupling the on-the-fly reduction with global quasi-steady-state approximation (QSSA) is developed. The proposed hybrid reduction scheme is demonstrated in various reactive flow simulations including zero-dimensional PFR model, multidimensional HCCI engine CFD model, and realistic gas phase injector CFD simulations. A flux-based quasi-steady-state (QSS) species selection procedure is introduced to facilitate the demonstration of hybrid scheme. Finally, a novel computational framework integrating automated mechanism generation and on-the-fly reduction is proposed and implemented using a stepwise integration. The proposed framework is then demonstrated in methane oxidation case studies and shows a new way of conducting reactive flow simulation without having an actual mechanism before the simulation starts. The integration of automated mechanism generation and on-the-fly reduction is a promising technique to perform reactive flow simulations and has the potential to reduce the computational cost of the simulations. The work in this dissertation provides powerful tools and important insight for the incorporation of detailed chemical kinetics in the reactive flow simulations.
