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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 computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty compression-ignition engine with a gasoline-like fuel that has an anti-knock index (AKI) of 58. The primary goal was to design an optimized combustion system utilizing the high volatility and low sooting tendency of the fuel for improved fuel efficiency with minimal hardware modifications to the engine. The CFD model predictions were first validated against experimental results generated using the stock engine hardware. A comprehensive design of experiments (DoE) study was performed at different operating conditions on a world-leading supercomputer, MIRA at Argonne National Laboratory, to accelerate the development of an optimized fuel-efficiency focused design while maintaining the engine-out NOx and soot emissions levels of the baseline production engine.

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).

With the development of advanced ABE fermentation technology, the volumetric percentage of acetone, butanol and ethanol in the bio-solvents can be precisely controlled. To seek for an optimized volumetric ratio for ABE-diesel blends, the previous work in our team has experimentally investigated and analyzed the combustion features of ABE-diesel blends with different volumetric ratio (A: B: E: 6:3:1; 3:6:1; 0:10:0, vol. %) in a constant volume chamber. It was found that an increased amount of acetone would lead to a significant advancement of combustion phasing whereas butanol would compensate the advancing effect. Both spray dynamic and chemistry reaction dynamic are of great importance in explaining the unique combustion characteristic of ABE-diesel blend. In this study, a semi-detailed chemical mechanism is constructed and used to model ABE-diesel spray combustion in a constant volume chamber.

The modeling of fuel jet atomization is key in the characterization of Internal Combustion (IC) engines, and 3D Computational Fluid Dynamics (CFD) is a recognized tool to provide insights for design and control purposes. Multi-hole injectors with counter-bored nozzle are the standard for Gasoline Direct Injection (GDI) applications and the Spray-G injector from the Engine Combustion Network (ECN) is considered the reference for numerical studies, thanks to the availability of extensive experimental data. In this work, the behavior of the Spray-G injector is simulated in a constant volume chamber, ranging from sub-cooled (nominal G) to flashing conditions (G2), validating the models on Diffused Back Illumination and Phase Doppler Anemometry data collected in vaporizing inert conditions.

This paper presents a computational fluid dynamics (CFD) study of the Engine Combustion Network (ECN) Spray G under non-vaporizing condition, focusing on the impacts of fuel properties as well as realistic geometry on the atomization process. The large-eddy-simulation method, coupled with the volume-of-fluid method, is used to model the high-speed turbulent two-phase flow. A moving-needle boundary condition is applied to capture the internal flow boundary condition accurately. The injector geometry was measured with micron-level resolution using x-ray tomographic imaging at the Advanced Photon Source at Argonne National Laboratory, providing detailed machining tolerance and defects from manufacturing and a realistic rough surface. A 2.5-μm fine mesh is used to sufficiently resolve the details of liquid-gas interface and the breakup process.

Recently, with the increasing interest on some potential alternative substitutes of petroleum fuels such as biodiesel and butanol, more and more researches are focused on the field of bio-fuels because they are renewable and friendly to the environment and can possibly reduce domestic demand on foreign petroleum. Bio-fuels are generally used in the commercial market by mixing with petroleum-based diesel or gasoline. Since the volatilities and boiling points of ethanol/butanol and diesel/biodiesel fuels are significantly different, micro-explosion can be expected in the blend mixture. In this study, a numerical model of micro-explosion including bubble generation, bubble expansion, and final breakup for multi-component bio-fuel droplets is proposed. From the simulated results of droplet characteristics at the onset of micro-explosion, it is concluded that micro-explosion is possible under engine operation condition for ethanol/butanol-diesel/biodiesel fuel blends.

The combustion and emission characteristics of a diesel engine running on butanol-diesel blends were investigated in this study. The blending ratio of n-butanol to diesel was varied from 0 to 40 vol% using an increment of 10 vol%, and each blend was tested on a 2.7 L V6 common rail direction injection diesel engine equipped with an EGR system. The test was carried out under two engine loads at a constant engine speed, using various combinations of EGR ratios and injection timings. Test results indicate that n-butanol addition to engine fuel is able to substantially decrease soot emission from raw exhaust gas, while the change in NOx emissions varies depending on the n-butanol content and engine operating conditions. Increasing EGR ratio and retarding injection timing are effective approaches to reduce NOx emissions from combustion of n-butanol-diesel blends.

It is challenging to develop highly efficient and clean engines while meeting user expectations in terms of performance, comfort, and drivability. One of the critical aspects in this regard is combustion noise control. Combustion noise accounts for about 40 percent of the overall engine noise in typical turbocharged diesel engines. The experimental investigation of noise generation is difficult due to its inherent complexity and measurement limitations. Therefore, it is important to develop efficient numerical strategies in order to gain a better understanding of the combustion noise mechanisms. In this work, a novel methodology was developed, combining computational fluid dynamics (CFD) modeling and genetic algorithm (GA) technique to optimize the combustion system hardware design of a high-speed direct injection (HSDI) diesel engine, with respect to various emissions and performance targets including combustion noise.

Knock is a major bottleneck to achieving higher thermal efficiency in spark ignition (SI) engines. The overall tendency to knock is highly dependent on fuel anti-knock quality as well as engine operating conditions. It is, therefore, critical to gain a better understanding of fuel-engine interactions in order to develop robust knock mitigation strategies. In the present work, a numerical model based on three-dimensional (3-D) computational fluid dynamics (CFD) was developed to capture knock in a Cooperative Fuel Research (CFR) engine. For combustion modeling, a hybrid approach incorporating the G-equation model to track turbulent flame propagation, and a homogeneous reactor multi-zone model to predict end-gas auto-ignition ahead of the flame front and post-flame oxidation in the burned zone, was employed.

Fuels in the gasoline auto-ignition range (Research Octane Number (RON) > 60) have been demonstrated to be effective alternatives to diesel fuel in compression ignition engines. Such fuels allow more time for mixing with oxygen before combustion starts, owing to longer ignition delay. Moreover, by controlling fuel injection timing, it can be ensured that the in-cylinder mixture is “premixed enough” before combustion occurs to prevent soot formation while remaining “sufficiently inhomogeneous” in order to avoid excessive heat release rates. Gasoline compression ignition (GCI) has the potential to offer diesel-like efficiency at a lower cost and can be achieved with fuels such as low-octane straight run gasoline which require significantly less processing in the refinery compared to today’s fuels.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Combustion systems with advanced injection strategies have been extensively studied, but there still exists a significant fundamental knowledge gap on fuel spray interactions with the piston surface and chamber walls. This paper is meant to provide detailed data on spray-wall impingement physics and support the spray-wall model development. The experimental work of spray-wall impingement with non-vaporizing spray characterization, was carried out in a high pressure-temperature constant-volume combustion vessel. The simultaneous Mie scattering of liquid spray and schlieren of liquid and vapor spray were carried out. Diesel fuel was injected at a pressure of 1500 bar into ambient gas at a density of 22.8 kg/m3 with isothermal conditions (fuel, ambient, and plate temperatures of 423 K). A Lagrangian-Eulerian modeling approach was employed to characterize the spray-gas and spray-wall interactions in the CONVERGETM framework by means of a Reynolds-Averaged Navier-Stokes (RANS) formulation.

Cyclic variability in internal combustion engines (ICEs) arises from multiple concurrent sources, many of which remain to be fully understood and controlled. This variability can, in turn, affect the behavior of the engine resulting in undesirable deviations from the expected operating conditions and performance. Shot-to-shot variation during the fuel injection process is strongly suspected of being a source of cyclic variability. This study focuses on the shot-to-shot variability of injector needle motion and its influence on the internal nozzle flow behavior using diesel fuel. High-speed x-ray imaging techniques have been used to extract high-resolution injector geometry images of the sac, orifices, and needle tip that allowed the true dynamics of the needle motion to emerge. These measurements showed high repeatability in the needle lift profile across multiple injection events, while the needle radial displacement was characterized by a much higher degree of randomness.

This paper focuses on detailed numerical simulations of direct injection diesel and gasoline sprays from production grade, multi-hole injectors. In a dual-fuel engine the direct injection of both the fuels can facilitate appropriate mixture preparation prior to ignition and combustion. Diesel and gasoline sprays were simulated using high-fidelity Large Eddy Simulations (LES) with the dynamic structure sub-grid scale model. Numerical predictions of liquid penetration, fuel density distribution as well as transverse integrated mass (TIM) at different axial locations versus time were compared against x-ray radiography data obtained from Argonne National Laboratory. A necessary, but often overlooked, criterion of grid-convergence is ensured by using Adaptive Mesh Refinement (AMR) for both diesel and gasoline. Nine different realizations were performed and the effects of random seeds on spray behavior were investigated.

The internal structure of Diesel fuel injectors is known to have a significant impact on the nozzle flow and the resulting spray emerging from each hole. In this paper the three-dimensional transient flow structures inside a Diesel injector is studied under nominal (in-axis) and realistic (including off-axis lateral motion) operating conditions of the needle. Numerical simulations are performed in the commercial CFD code CONVERGE, using a two-phase flow representation based on a mixture model with Volume of Fluid (VOF) method. Moving boundaries are easily handled in the code, which uses a cut-cell Cartesian method for grid generation at run time. First, a grid sensitivity study has been performed and mesh requirements are discussed. Then the results of moving needle calculations are discussed. Realistic radial perturbations (wobbles) of the needle motion have been applied to analyze their impact on the nozzle flow characteristics.

This paper focuses on the spray and atomization characteristics of a Dual-Fuel Injector (DFI) which includes a primary and a secondary fuel inlet. Three injectors were analyzed in this study. Apart from the DFI, two conventional diesel injectors were tested as baselines for comparison - a piezo-electric and a solenoid injector. The rail pressures ranged from 200 - 500 bar for the conventional injectors. The DFI was tested first as a single-fuel injector (by sealing the secondary inlet) at pressures ranging from 100 - 300 bar, and then in its dual-fuel mode with the primary inlet pressure ranging from 100 - 300 bar, and the secondary inlet at 25 bar higher than the primary pressure. Injection duration of 0.5 ms was chosen for the experiment. High-speed Mie scattering images were recorded to capture the spray evolution. Phase Doppler Anemometry (PDA) measurements were conducted at different locations in the spray for the acquisition of droplet sizes and velocity distributions.

An optically accessible single-cylinder high-speed direct-injection (HSDI) diesel engine equipped with a Bosch common rail injection system was used to study effects of injection pressures on the in-cylinder spray and combustion processes. An injector with an injection angle of 70 degrees and European low sulfur diesel fuel (cetane number 54) were used in the work. The operating load was 2.0 bar IMEP with no EGR added in the intake. The in-cylinder pressure was measured and the heat release rate was calculated. High-speed Mie-scattering technique was employed to visualize the liquid distribution and evolution. High-speed combustion video was also captured for all the studied cases using the same frame rate. NOx emissions were measured in the exhaust pipe. The experimental results indicated that for all of the conditions the heat release rate was dominated by a premixed combustion pattern. Two-stage low temperature reaction was seen for early injection timings.

Dual-fuel combustion combining a premixed charge of compressed natural gas (CNG) and a pilot injection of diesel fuel offer the potential to reduce diesel fuel consumption and drastically reduce soot emissions. In this study, dual-fuel combustion using methane ignited with a pilot injection of No. 2 diesel fuel, was studied in a single cylinder diesel engine with optical access. Experiments were performed at a CNG substitution rate of 70% CNG (based on energy) over a wide range of equivalence ratios of the premixed charge, as well as different diesel injection strategies (single and double injection). A color high-speed camera was used in order to identify and distinguish between lean-premixed methane combustion and diffusion combustion in dual-fuel combustion. The effect of multiple diesel injections is also investigated optically as a means to enhance flame propagation towards the center of the combustion chamber.

A new approach of NOx reduction in the compression-ignition engine is introduced in this work. The previous research has shown that during the combustion stage, the high temperature ignition tends to occur early at the near-stoichiometric region where the combustion temperature is high and majority of NOx is formed; Therefore, it is desirable to burn the leaner region first and then the near-stoichiometric region, which inhibits the temperature rise of the near-stoichiometric region and consequently suppresses the formation of NOx. Such inverted ignition sequence requires mixture with inverted phi-sensitivity. Fuel selection is performed based on the criteria of strong ignition T-sensitivity, negligible negative temperature coefficient (NTC) behavior, and large heat of vaporization (HoV).