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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).

Caterpillar Fuel Systems is developing a family of next generation electronic unit injectors that provide the fundamental injection characteristics necessary for emissions and performance improvements for future direct-injection diesel engines. This paper describes the development and design of the mechanically actuated version of Caterpillar's advanced electronic unit injector fuel system to meet the engine customer driven requirements for enhanced injection characteristics with reliability and durability improvements.

The critical particle size for a high-pressure injection system was determined. Various double-cut test dusts ranging from 0 to 5 μm to 10 to 20 μm were evaluated to determine which test dust caused the high-pressure system to fail. With the exception of the 0- to 5-μm test dust, all test dust ranges caused failure in the high-pressure injection system. Analysis of these evaluations revealed that the critical particle size, in initiating significant abrasive wear, is 6 to 7 μm. Wear curve formulas were generated for each evaluation. A formula was derived that allows the user to determine if the fuel filter effluent will cause harmful damage to the fuel system based on the number of 5-, 10-, and 15-μm particles per milliliter present. A methodology was developed to evaluate fuel filter performance as related to engine operating conditions. The abrasive methodology can evaluate online filter efficiency and associated wear in a high-pressure injection system.

The current study was focused on flow field measurements of diesel sprays. The global fuel spray characteristics, such as spray penetration, have also been measured. Particle Image Velocimetry (PIV) was utilized for flow field measurements and the global spray characteristics were recorded with high-speed back light photographing. The flow field was scanned to get an idea of the compatibility of PIV technique applied to dense and high velocity sprays. It is well proven that the PIV technique can be utilized at areas of low number density of droplets, but the center of the spray is way beyond the ideal PIV measurement conditions. The depth at which accurate flow field information can be gathered was paid attention to.

This study presents diesel spray breakup regimes and the wave model basic theory from literature. The RD wave model and the KH-RT wave model are explained. The implementation of the KH-RT wave model in a commercial CFD code is briefly presented. This study relies on experimental data from non-evaporating sprays that have earlier been measured at Helsinki University of Technology. The simulated fuel spray in a medium-speed diesel engine had a satisfactory match with the experimental data. The KH-RT wave model resulted in a much faster drop breakup than with the RD wave model. This resulted in a thin spray core with the KH-RT model. The fuel viscosity effect on drop sizes was well predicted by the KH-RT wave model.

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.

Cylinder charge, cylinder flow field and fuel injection play the dominant roles in controlling combustion in compression ignition engines. Respective computational cylinder charge, initial flow field and fuel injection boundary affect combustion simulation and the quality of emission prediction. In this study the means of generating the initial values and boundary data are presented and the effect of different methods is discussed. This study deals with three different compression ignition engines with cylinder diameters of 111, 200 and 460 mm. The initial cylinder charge has been carefully analyzed through gas exchange pressure recordings and corresponding 1-dimensional simulation. The swirl generated by intake ports in a high-speed engine is simulated and measured. The combustion simulation using a whole cylinder model was compared with a sector model simulation result.

The objective of this study was to build up an optical access into a large bore medium-speed research engine and carry out the first fuel spray Particle Image Velocimetry (PIV) measurements in the running large bore medium-speed engine in high pressure environment. The aim was also to measure spray penetration with same optical access and apparatus. The measurements were performed in a single-cylinder large bore medium-speed research engine, the Extreme Value Engine (EVE) with optical access into the combustion chamber. The authors are not aware of any other studies on optical spray measurements in large bore medium-speed diesel engines. Successful optical measurements of the fuel spray penetration and the velocity fields were carried out. This confirms that the exceptional component design and laser sheet alignment used in this study proved to be valid for optical fuel spray measurements in large-bore medium-speed diesel engines.

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.

Hydrotreating of vegetable oils or animal fats is an alternative process to esterification for producing biobased diesel fuels. Hydrotreated products are also called renewable diesel fuels. Hydrotreated vegetable oils (HVO) do not have the detrimental effects of ester-type biodiesel fuels, like increased NOx emission, deposit formation, storage stability problems, more rapid aging of engine oil or poor cold properties. HVOs are straight chain paraffinic hydrocarbons that are free of aromatics, oxygen and sulfur and have high cetane numbers. In this paper, NOx - particulate emission trade-off and NOx - fuel consumption trade-off are studied using different fuel injection timings in a turbocharged charge air cooled common rail heavy duty diesel engine. Tested fuels were sulfur free diesel fuel, neat HVO, and a 30% HVO + 70% diesel fuel blend. The study shows that there is potential for optimizing engine settings together with enhanced fuel composition.