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The current trend of downsizing used in gasoline engines, while reducing fuel consumption and CO2 emissions, imposes severe thermal loads inside the combustion chamber. These critical thermodynamic conditions lead to the possible auto-ignition (AI) of fresh gases hot-spots around Top-Dead-Center (TDC). At this very moment where the surface to volume ratio is high, wall heat transfer influences the temperature field inside the combustion chamber. The use of a realistic wall temperature distribution becomes important in the case of a downsized engine where fresh gases hot spots found near high temperature walls can initiate auto-ignition. This paper presents a comprehensive numerical methodology for an accurately prediction of thermodynamic conditions inside the combustion chamber based on Conjugate Heat Transfer (CHT).

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 Relevant published and unpublished work from prior ECN workshops is reviewed.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.

Reynolds-averaged Navier-Stokes (RANS) modeling is expected to deliver an ensemble-averaged result for the majority of turbulent flows. This could lead to the conclusion that multi-cycle internal combustion engine (ICE) simulations performed using RANS must exhibit a converging numerical solution after a certain number of consecutive cycles. However, for some engine configurations unsteady RANS simulations are not guaranteed to deliver an ensemble-averaged result. In this paper it is shown that, when using RANS modeling to simulate multiple engine cycles, the cycle-to-cycle variations (CCV) generated from different initial conditions at each cycle are not damped out even after a large number of cycles. A single-cylinder GDI research engine is simulated using RANS modeling and the numerical results for 20 consecutive engine cycles are evaluated for two specific operating conditions.

This paper is part of a larger body of experimental and computational work devoted to studying the role of close-coupled post injections on soot reduction in a heavy-duty optical engine. It is a continuation of an earlier computational paper. The goals of the current work are to develop new CFD analysis tools and methods and apply them to gain a more in depth understanding of the different in-cylinder environments into which fuel from main- and post-injections are injected and to study how the in-cylinder flow, thermal and chemical fields are transformed between start of injection timings. The engine represented in this computational study is a single-cylinder, direct-injection, heavy-duty, low-swirl engine with optical components. It is based on the Cummins N14, has a cylindrical shaped piston bowl and an eight-hole injector that are both centered on the cylinder axis. The fuel used was n-heptane and the engine operating condition was light load at 1200 RPM.

Due to the new challenge of meeting number-based regulations for particulate matter (PM), a numerical and experimental study has been conducted to better understand particulate formation in engines fuelled with compressed natural gas. The study has been conducted on a Heavy-Duty, Euro VI, 4-cylinder, spark ignited engine, with multipoint sequential phased injection and stoichiometric combustion. For the experimental measurements two different instruments were used: a condensation particle counter (CPC) and a fast-response particle size spectrometer (DMS) the latter able also to provide a particle size distribution of the measured particles in the range from 5 to 1000 nm. Experimental measurements in both stationary and transient conditions were carried out. The data using the World Harmonized Transient Cycle (WHTC) were useful to detect which operating conditions lead to high numbers of particles. Then a further transient test was used for a more detailed and deeper analysis.

Reactivity Controlled Compression Ignition (RCCI) has been shown to be an attractive concept to achieve clean and high efficiency combustion. RCCI can be realized by applying two fuels with different reactivities, e.g., diesel and gasoline. This motivates the idea of using a single low reactivity fuel and direct injection (DI) of the same fuel blended with a small amount of cetane improver to achieve RCCI combustion. In the current study, numerical investigation was conducted to simulate RCCI and HCCI combustion and emissions with various fuels, including gasoline/diesel, iso-butanol/diesel and iso-butanol/iso-butanol+di-tert-butyl peroxide (DTBP) cetane improver. A reduced Primary Reference Fuel (PRF)-iso-butanol-DTBP mechanism was formulated and coupled with the KIVA computational fluid dynamic (CFD) code to predict the combustion and emissions of these fuels under different operating conditions in a heavy duty diesel engine.

Due to the upcoming regulations for particulate matter (PM) emissions from GDI engines, a computational fluid dynamic (CFD) modeling study to predict soot emissions (both mass and solid particle number) from gasoline direct injection (GDI) engines was undertaken to provide insights on how and why soot emissions are formed from GDI engines. In this way, better methods may be developed to control or reduce PM emissions from GDI engines. In this paper, the influence of engine operating parameters was examined for a side-mounted fuel injector configuration in a direct-injection spark-ignition (DISI) engine. The present models are able to reasonably predict the influences of the variables of interest compared to available experimental data or literature. For a late injection strategy, effects of the fuel composition, and spray cone angle were investigated with a single-hole injector.

In this work computational and experimental approaches are combined to characterize in-cylinder flow structures and local flow field properties during operation of the Sandia 1.9L light-duty optical Diesel engine. A full computational model of the single-cylinder research engine was used that considers the complete intake and exhaust runners and plenums, as well as the adjustable throttling devices used in the experiments to obtain different swirl ratios. The in-cylinder flow predictions were validated against an extensive set of planar PIV measurements at different vertical locations in the combustion chamber for different swirl ratio configurations. Principal Component Analysis was used to characterize precession, tilting and eccentricity, and regional averages of the in-cylinder turbulence properties in the squish region and the piston bowl.

The application of close-coupled post injections in diesel engines has been proven to be an effective in-cylinder strategy for soot reduction, without much fuel efficiency penalty. But due to the complexity of in-cylinder combustion, the soot reduction mechanism of post-injections is difficult to explain. Accordingly, a simulation study using a three dimensional computational fluid dynamics (CFD) model, coupled with the SpeedChem chemistry solver and a semi-detailed soot model, was carried out to investigate post-injection in a constant volume combustion chamber, which is more simple and controllable with respect to the boundary conditions than an engine. A 2-D axisymmetric mesh of radius 2 cm and height 5 cm was used to model the spray. Post-injection durations and initial oxygen concentrations were swept to study the efficacy of post-injection under different combustion conditions.

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as local, globally lean, low-temperature combustion strategies are setting the path towards a more efficient and environmentally sustainable use of energy resources in transportation. In this paper, we assessed the computational efficiency of a recently developed sparse analytical Jacobian chemistry solver, namely ‘SpeedCHEM’, that features both direct and Krylov-subspace solution methods for maximum efficiency for both small and large mechanism sizes. The code was coupled with a high-dimensional clustering algorithm for grouping homogeneous reactors into clusters with similar states and reactivities, to speed-up the chemical kinetics solution in multi-dimensional combustion simulations.

One in-cylinder strategy for reducing soot emissions from diesel engines while maintaining fuel efficiency is the use of close-coupled post injections, which are small fuel injections that follow the main fuel injection after a short delay. While the in-cylinder mechanisms of diesel combustion with single injections have been studied extensively and are relatively well understood, the in-cylinder mechanisms affecting the performance and efficacy of post injections have not been clearly established. Here, experiments from a single-cylinder heavy-duty optical research engine incorporating close- coupled post injections are modeled with three dimensional (3D) computational fluid dynamics (CFD) simulations. The overall goal is to complement experimental findings with CFD results to gain more insight into the relationship between post-injections and soot. This paper documents the first stage of CFD results for simulating and analyzing the experimental conditions.

Shock waves have been recently observed in high-pressure diesel sprays. In this paper, three-dimensional numerical simulations of supersonic diesel spray injection have been performed to investigate the underlying dynamics of the induced shock waves and their interactions with the spray. A Volume-of-Fluid based method in the CFD software (CONVERGE) is used to model this multiphase phenomena. An adaptive Mesh Refinement (AMR) scheme is employed to capture the front of the spray and the shock waves with high fidelity. Simulation results are compared to the available experimental observations to validate the numerical procedure. Parametric studies with different injection and ambient conditions are conducted to examine the effect of these factors on the generation of shock waves and their dynamics.

Real transportation fuels, such as gasoline and diesel, are mixtures of thousands of different hydrocarbons. For multidimensional engine applications, numerical simulations of combustion of real fuels with all of the hydrocarbon species included exceeds present computational capabilities. Consequently, surrogate fuel models are normally utilized. A good surrogate fuel model should approximate the essential physical and chemical properties of the real fuel. In this work, we present a novel methodology for the formulation of surrogate fuel models based on local optimization and sensitivity analysis technologies. Within the proposed approach, several important fuel properties are considered. Under the physical properties, we focus on volatility, density, lower heating value (LHV), and viscosity, while the chemical properties relate to the chemical composition, hydrogen to carbon (H/C) ratio, and ignition behavior. An error tolerance is assigned to each property for convergence checking.

In this paper, we studied the accuracy of computational modeling of the ignition of a pilot injectionin the Sandia National Laboratories (SNL) light-duty optical engine facility, using the physical properties of a cetane/iso-cetane Diesel Primary Reference Fuel (DPRF) mixture and the reaction kinetics of a well-validated mechanism for primary reference fuels. Local fuel-air equivalence ratio measurements from fuel tracer based planar laser-induced fluorescence (PLIF) experiments were used to compare the mixture formation predictions with KIVA-ERC-based simulations. The effects of variations in injection mass from 1 mg to 4 mg, in-cylinder swirl ratio, and near-TDC temperatures on non-combusting mixture preparation were analyzed, to assess the accuracy of the model in capturing average jet behavior, despite its inability to model the non-negligible jet-by-jet variations seen in the experiments.

Combustion is governed by only two phenomena: chemical reactions and mixing (i.e., transport of energy, species, and momentum). A Reynolds Averaged Navier-Stokes (RANS) turbulence model is commonly employed to account for the enhanced mixing due to the presence of turbulence in fluid flow. A RANS turbulence model enhances mixing by introducing a turbulent viscosity. The addition of a turbulent viscosity not only enhances mixing but it also eliminates smaller scales in the CFD simulation. Even though the turbulent viscosity eliminates smaller scales, it is common for RANS engine combustion simulations to be under-resolved. The lack of sufficient mesh resolution to resolve the remaining scales in a RANS combustion simulation may result in a significant sub-grid term that needs to be modeled. In the context of combustion simulation, it is shown that frequently this sub-grid term is significantly more important than Turbulent Chemistry Interaction terms (TCI).

3-D Computational Fluid Dynamics (CFD) simulations have been performed to study particulate formation in a Spark-Ignition (SI) engine under premixed conditions. A semi-detailed soot model and a chemical kinetic model, including poly-aromatic hydrocarbon (PAH) formation, were coupled with a spark ignition model and the G equation flame propagation model for SI engine simulations and for predictions of soot mass and particulate number density. The simulation results for in-cylinder pressure and particle size distribution (PSDs) are compared to available experimental studies of equivalence ratio effects during premixed operation. Good predictions are observed with regard to cylinder pressure, combustion phasing and engine load. Qualitative agreements of in-cylinder particle distributions were also obtained and the results are helpful to understand particulate formation processes.

The effects of different Research Octane Number [RON] fuels on a multi-cylinder light-duty compression ignition [CI] engine were investigated at light load conditions. Experiments were conducted on a GM 1.9L 4-cylinder diesel engine at Argonne National Laboratory, using two different fuels, i.e., 75 RON and 93 RON. Emphasis was placed on 5 bar BMEP load, 2000 rev/min engine operation using two different RON fuels, and 2 bar BMEP load operating at 1500 rev/min using 75 RON gasoline fuel. The experiments reveal difficulty in controlling combustion at low load points using the higher RON fuel. In order to explain the experimental trends, simulations were carried out using the KIVA3V-Chemkin Computational Fluid Dynamics [CFD] Code. The numerical results were validated with the experimental results and provided insights about the engine combustion characteristics at different speeds and low load conditions using different fuels.

In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.

A comprehensive biodiesel combustion model is presented for use in multi-dimensional engine simulations. The model incorporates realistic physical properties in a vaporization model developed for multi-component fuel sprays and applies an improved mechanism for biodiesel combustion chemistry. Previously, a detailed mechanism for methyl decanoate and methyl-9-decenoate was reduced from 3299 species to 85 species to represent the components of biodiesel fuel. In this work, a second reduction was performed to further reduce the mechanism to 69 species. Steady and unsteady spray simulations confirmed that the model adequately reproduced liquid penetration observed in biodiesel spray experiments. Additionally, the new model was able to capture expected fuel composition effects with low-volatility components and fuel blend sprays penetrating further.

The present experimental study explored methods to obtain the maximum practical cycle efficiency with Reactivity Controlled Compression Ignition (RCCI). The study used both zero-dimensional computational cycle simulations and engine experiments. The experiments were conducted using a single-cylinder heavy-duty research diesel engine adapted for dual fuel operation, with and without piston oil gallery cooling. In previous studies, RCCI combustion with in-cylinder fuel blending using port-fuel-injection of a low reactivity fuel and optimized direct-injections of higher reactivity fuels was demonstrated to permit near-zero levels of NOx and PM emissions in-cylinder, while simultaneously realizing gross indicated thermal efficiencies in excess of 56%. The present study considered RCCI operation at a fixed load condition of 6.5 bar IMEP an engine speed of 1,300 [r/min]. The experiments used a piston with a flat profile with 18.7:1 compression ratio.