Title: Multiphysical Modelling of Regular and Irregular Combustion in Spark Ignition Engines using an Integrated / Interactive Flamelet Approach
Publisher: Logos Verlag Berlin
Publication Date: 2013
Language: English
ISBN 10: 3832534261
ISBN 13: 9783832534264
Binding: paperback
Condition: New
Weight: 17 ounces

About this title

Synopsis

The virtual development of future Spark Ignition (SI) engine combustion processes in three-dimensional Computational Fluid Dynamics (3D-CFD) demands for the integration of detailed chemistry, enabling - additionally to the 3D-CFD modelling of flow and mixture formation - the prediction of fuel-dependent SI engine combustion in all of its complexity. This work presents an approach, which constitutes a coupled solution for flame propagation, auto-ignition, and emission formation modelling incorporating detailed chemistry, while exhibiting low computational costs. For modelling the regular flame propagation, a laminar flamelet approach, the G-equation is used. Auto-ignition phenomena are addressed using an integrated flamelet approach, which bases on the tabulation of fuel-dependent reaction kinetics. By introducing a progress variable for the auto-ignition - the Ignition Progress Variable (IPV) - detailed chemistry is integrated in 3D-CFD. The modelling of emission formation bases on an interactively coupled flamelet approach, the Transient Interactive Flamelet (TIF) model. The functionality of the combined approach to model the variety of SI engine combustion phenomena is proved first in terms of fundamentals and standalone sub-model functionality studies by introducing a simplified test case, which represents an adiabatic pressure vessel without moving meshes. Following the basic functionality studies, the sub-model functionalities are investigated and validated in adequate engine test cases. It is shown, that the approach allows to detect locally occurring auto-ignition phenomena in the combustion chamber, and to model their interaction with regular flame propagation. Moreover, the approach enables the prediction of emission formation on cell level.

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