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This paper implements a coupled approach to integrate the internal nozzle flow and the ensuing fuel spray using a Volume-of-Fluid (VOF) method in the CONVERGE CFD software. A VOF method was used to model the internal nozzle two-phase flow with a cavitation description closed by the homogeneous relaxation model of Bilicki and Kestin [1]. An Eulerian single velocity field approach by Vallet et al. [2] was implemented for near-nozzle spray modeling. This Eulerian approach considers the liquid and gas phases as a complex mixture with a highly variable density to describe near nozzle dense sprays. The mean density is obtained from the Favreaveraged liquid mass fraction. The liquid mass fraction is transported with a model for the turbulent liquid diffusion flux into the gas.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

The current study utilized 3-D computational fluid dynamics (CFD) combustion analysis to guide the development of a viable full load range combustion strategy in a light-duty gasoline compression ignition (GCI) engine. A higher reactivity gasoline that has a research octane number (RON) of 70 was used for the combustion strategy development. The engine has a geometric compression ratio of 14.5 with a piston bowl designed to accommodate different combustion strategies and injector spray patterns. Detailed combustion optimization was focused on 6 and 18 bar gross indicated mean effective pressure (IMEPg) at 1500 rpm through a Design of Experiments approach. Two different strategies were investigated: (a) a late triggering fuel injection with a wide spray angle (combustion strategy #1); and (b) an early triggering fuel injection with a narrow spray angle (combustion strategy #2).

The accurate modeling of fuel spray behavior under diesel engine conditions requires well-characterized boundary conditions. Among those conditions, the spray cone angle is important due to its impact on the spray mixing process, flame lift-off locations and subsequent soot formation. The spray cone angle is a highly dynamic variable, but existing correlations have been developed mainly for diesel fuels at quasi-steady state and relatively low injection pressures. The objective of this study was to develop spray cone angle correlations for both diesel and a light-end gasoline fuel over a wide range of diesel-engine operating conditions that are capable of capturing both the transient and quasi-steady state processes. Two important macroscopic characteristics of solid cone sprays, the spray cone angle and spray penetration, were measured using a single-hole heavy-duty injector using two fuels at diesel engine conditions in an optical constant volume vessel.

Recent research has shown that gasoline compression ignition (GCI) improves the soot-NOx tradeoff of traditional diesel engines due to the beneficial properties of light distillate fuels. However, system level optimization of a new engine concept is ultimately needed to maximize fuel economy and emissions improvements. Along with air and aftertreatment systems, the fuel system also requires further development to enable GCI. One important design tool for fuel system hardware is 1-D hydraulic modeling. Although accurate tabulations of diesel or equivalent calibration fluid properties are available in 1-D modelling software packages, the same situation does not exist for gasoline-like fuels, especially at conditions encountered in the high-pressure injection equipment needed to support GCI. This study presents a methodology for generating accurate liquid property databases of complex, multi-component light distillate fuels that can be used in high-pressure 1-D hydraulic models.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NOx within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions.

A PPCI-diffusion combustion strategy has shown the potential to achieve high efficiency, clean gasoline compression ignition (GCI) combustion across the full engine operating range. By conducting a 3-D CFD-led combustion system design campaign, this investigation was focused on developing a next generation (NextGen), step-lipped piston design concept in a 2.6L advanced light-duty GCI engine. Key geometric features of the NextGen piston bowl were parametrized and studied with customized spray targeting. A low lip positioning design with 128° spray targeting was found to provide the best performance. Fuel injection strategy optimization was performed at a full-load operating point (OP), 2000 rpm/24 bar closed-cycle IMEP (IMEPcc).