Search Results

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.

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).

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

A new camless system (referred to as Hydraulic Valve Control - HVC - system) is in an advanced state of prototyping and development. The present paper aims to support the new incoming activities concerning the possible modifications to the geometrical and mechanical characteristics of the system. The optimization of the new HVC system prototype is done using a multi-objective tool that integrates the hydraulic/mechanical simulator reproducing the physical model, with an optimization software. The latter tool can be used choosing a specific approach among different probabilistic mathematical models; the Genetic Algorithm approach was chosen to achieve the goal of the present study. The paper describes design optimization of the pilot stage of the actuator for given characteristics of the power stage and of the poppet valve.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

For several years there has been a great deal of effort made in researching ways to run a compression ignition engine with simultaneously high efficiency and low emissions. Recently much of this focus has been dedicated to using gasoline-like fuels that are more volatile and less reactive than conventional diesel fuel to allow the combustion to be more premixed. One of the key challenges to using fuels with such properties in a compression ignition engine is stable engine operation at low loads. This paper provides an analysis of how stable gasoline compression ignition (GCI) engine operation was achieved down to idle speed and load on a multi-cylinder compression ignition engine using only 87 anti-knock index (AKI) gasoline. The variables explored to extend stable engine operation to idle included: uncooled exhaust gas recirculation (EGR), injection timing, injection pressure, and injector nozzle geometry.

Spray modeling techniques have evolved from the classic DDM (Discrete Drops Method) approach, where the continuous liquid jet is discretized into “drops” or “parcels” till advanced spray models often based on Eulerian approaches. The former technique, although computationally efficient, is essentially inadequate in highly dense jets, as in the near nozzle region of compression ignition engines, while the latter could lead to extreme levels of computational effort when resolved interface capturing methods, such as VoF (Volume of Fluids) and LS (Level-Set) types, are used. However, in a typical engineering calculation, the mesh resolution is considerably coarser than in these high fidelity computations. If one presumes that these interfacial details are far smaller than the mesh size, smoothing features over at least one cell ultimately results in a diffuse-interface treatment in a Eulerian framework.

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.

The aim of the paper is the comparison of the injection process with different fuels, i.e. a standard diesel fuel and a pure biodiesel. Multiphase cavitating flows inside diesel nozzles are analyzed by means of unsteady CFD simulations using a two-fluid approach with consideration of bubble dynamics, on moving grids from needle opening to closure. Two five-hole nozzles with cylindrical and conical holes are studied and their behaviors are discussed taking into account the different properties of the two fuels. Extent of cavitation regions is not much affected by the fuel type. Biodiesel leads to significantly higher mass flow only if the nozzle design induces significant cavitation which extends up to the outlet section and if the injector needle is at high lift. If the internal hole shaping is able to suppress cavitation, the stabilized mass flows are very similar with both fuels.

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.

The basic idea behind large-eddy simulation (LES) is to accurately resolve the large energy-containing scales and to use subgrid-scale (SGS) models for the smaller scales. The accuracy of LES can be significantly impacted by the numerical discretization schemes and the choice of the SGS model. This work investigates the accuracy of low-order LES codes in the simulation of a turbulent round jet which is representative of fuel jets in engines. The turbulent jet studied is isothermal with a Reynolds number of 6800. It is simulated using Converge, which is second-order accurate in space and first-order in time, and FLEDS, developed at Purdue University, which is sixth-order accurate in space and fourth-order in time. The high-order code requires the resolution of acoustic time-scales and hence is approximately 10 times more expensive than the low-order code.

Water injection in highly boosted gasoline direct injection (GDI) engines has become an attractive area over the last few years as a way of increasing efficiency, enhancing performance and reducing emissions. The technology and its effects are not new, but current gasoline engine trends for passenger vehicles have several motivations for adopting this technology today. Water injection enables higher compression ratios, optimal spark timing and elimination of fuel enrichment at high load, and possibly replacement of EGR. Physically, water reduces charge temperature by evaporation, dilutes combustion, and varies the specific heat ratio of the working fluid, with complex effects. Several of these mutually intertwined aspects are investigated in this paper through computational fluid dynamics (CFD) simulations, focusing on a turbo-charged GDI engine with port water injection (PWI). Different strategies for water injection timing, pressure and spray targeting are investigated.

Emission legislation for passenger cars is requiring a drastic reduction of exhaust pollutants from internal combustion engines (ICE). In this framework, achieving a quick heating-up of the catalyst is of paramount importance to cut down the cold start emissions and meet future regulation requirements. This paper describes the development and the basic characteristics of a novel burner for gasoline engines exhaust systems designed for being activated immediately at engine cold start. The burner is comprised of a fuel injector, an air system, and an ignition device. The design of the combustion chamber is first presented, with a description of the air-fuel interactions and mixture formation processes. Swirl is used along with a flame-holder concept to anchor the flame at the mixer exit. Spray-swirl and spray-walls interaction are also discussed. Computational Fluid Dynamics (CFD) analyses have been used to investigate these aspects.

Natural gas (NG) is an alternative fuel for spark-ignition engines. In addition to its cleaner combustion, recent breakthroughs in drilling technologies increased its availability and lowered its cost. NG consists of mostly methane, but it also contains heavier hydrocarbons and inert diluents, the levels of which vary substantially with geographical source, time of the year and treatments applied during production or transportation. To investigate the effects of NG composition on engine performance and emissions, a 3D CFD model of a heavy-duty diesel engine retrofitted to NG spark ignition simulated lean-combustion engine operation at low speed and medium load conditions. The work investigated three NG blends with similar lower heating value (i.e., similar energy density) but different Methane Number (MN). The results indicated that a lower MN increased flame propagation speed and thus increased in-cylinder pressure and indicated mean effective pressure.

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 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.

It has been proved that Radio Frequency Corona, among other innovative ignition systems, is able to stabilize combustion and to extend the engine operating range in lean conditions, with respect to conventional spark igniters. This paper reports on a sensitivity analysis on the combustion behavior for different values of Corona electric control parameters (supply voltage and discharge duration). Combustion analysis has been carried out on a single cylinder PFI gasoline-fueled optical engine, by means of both indicating measurements and imaging. A high-speed camera has been used to record the natural luminosity of premixed flames and the obtained images have been synchronized with corresponding indicating acquisition data. Imaging tools allowed to observe and measure the early flame development, providing information which are not obtainable by a pressure-based indicating system.

In this study, the combustion system of a light-duty compression ignition engine running on a market gasoline fuel with Research Octane Number (RON) of 91 was optimized using computational fluid dynamics (CFD) and Machine Learning (ML). This work was focused on optimizing the piston bowl geometry at two compression ratios (CR) (17 and 18:1) and this exercise was carried out at full-load conditions (20 bar indicated mean effective pressure, IMEP). First, a limited manual piston design optimization was performed for CR 17:1, where a couple of pistons were designed and tested. Thereafter, a CFD design of experiments (DoE) optimization was performed where CAESES, a commercial software tool, was used to automatically perturb key bowl design parameters and CONVERGE software was utilized to perform the CFD simulations. At each compression ratio, 128 piston bowl designs were evaluated.

The primary objective of the research discussed here was to compare the commercial computational fluid dynamics (CFD) software, CONVERGE, and a prevalent open-source code, OpenFOAM, with regard to their ability to predict spray and combustion characteristics. The high-fidelity data were obtained from the Engine Combustion Network (ECN) at Sandia National Laboratory in a constant-volume combustion vessel under well-defined, controlled conditions. The experiments and simulations were performed by using two diesel surrogate fuels (i.e., n-heptane and n-dodecane) under both non-reacting and reacting conditions. Specifically, ECN data on spray penetration, liquid length, vapor penetration, mixture fraction, ignition delay, and flame lift-off length (LOL) were used to validate both codes. Results indicate that both codes can predict the above experimental characteristics very well.

It is well known that in-nozzle flow behavior can significantly influence the near-nozzle spray formation and mixing that in turn affect engine performance and emissions. This in-nozzle flow behavior can, in turn, be significantly influenced by fuel properties. The goal of this study is to characterize the behavior of two different fuels, namely, a straight-run naphtha that has an anti-knock index of 58 (denoted as “Full-Range Naphtha”) and n-dodecane, in a simulated multi-hole common-rail diesel fuel injector. Simulations were carried out using a fully compressible multi-phase flow representation based on the mixture model assumption with the Volume of Fluid method. Our previous studies have shown that the characteristics of internal and near-nozzle flow are strongly related to needle motion in both the along- and off-axis directions.