Turbulence-chemistry interactions in CFD modelling of diesel engines

Abstract

The use of detailed mechanisms is indispensable in predicting intermediate species in practical combustion devices. Detailed mechanisms describing ignition, flame propagation and pollutant formation typically involve several hundred species and elementary reactions. Their size makes it prohibitive to use them in three-dimensional combustion simulations of real-life equipment. Conventionally reduced mechanisms often fail to predict minor radicals and pollutant precursors. In such situations, the ILDM (Intrinsic Low Dimensional Manifold) method gives an effective way of coupling the details of complex chemistry with the time variations due to turbulence. It is a method of automatic reduction of a detailed mechanism, which assumes local equilibrium with respect to the fastest time-scales identified by a local eigenvector analysis.

The KIVA-III code is used to simulate the flow in a single cylinder of a DI diesel engine. A RNG (Renormalized Group Theory) k-ε model is added to the code to model the turbulent flow field. Turbulence–chemistry interactions are taken into account by integrating the chemical source terms over a presumed probability density function (PDF). A standard approach can lead to unphysical states and rather poor heat-release and temperature profiles. An improvised approach to eliminate this problem is outlined in this work. Since no equilibrium or partial-equilibrium approach for mechanism reduction is involved, accurate concentrations of intermediate species such as O radicals and soot-precursors (C₂H₂ and C₃H₃) can be obtained from the ILDM. This improves the accuracy of pollutant predictions. The goal of this work is to establish the methods used as industrially acceptable ways of coupling the chemistry with turbulence.

Keywords:

• Intrinsic low dimensional manifolds
• diesel engine
• computational fluid dynamics
• turbulence-chemistry interactions
• automatically reduced reaction mechanisms