Search Results

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

The discrete droplet model is widely used to describe two-phase flows such as high-velocity dense sprays. The interaction between the liquid and the gas phase is modeled via appropriate source terms in the gas phase equations. This approach can lead to a strong dependence of the liquid-gas coupling on the spatial resolution of the gas phase. The liquid-gas coupling requires the computation of source terms using the gas phase properties, and, subsequently, these sources are then distributed onto the gas phase mesh. In this study, a Lagrange polynomial interpolation method has been developed to evaluate the source terms and also to distribute these source terms onto the gas mesh. The focus of this investigation has been on the momentum exchange between the two phases. The Lagrange polynomial interpolation and source term distribution methods are evaluated for non-evaporating sprays using KIVA3 as a modeling platform.

A KIVA-based CFD tool has been utilized to simulate the effect of a Common-Rail injection system applied to a large, uniflow-scavenged, two-stroke diesel engine. In particular, predictions for variations of injection pressure and injection duration have been validated with experimental data. The computational models have been evaluated according to their predictive capabilities of the combustion behavior reflected by the pressure and heat release rate history and the effects on nitric oxide formation and wall temperature trends. In general, the predicted trends are in good agreement with the experimental observations, thus demonstrating the potential of CFD as a design tool for the development of large diesel engines equipped with Common-Rail injection. Existing deficiencies are identified and can be explained in terms of model limitations, specifically with respect to the description of turbulence and combustion chemistry.