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The effect of injection pressure ranging from 100 to 300MPa on the ignition, flame development and soot formation characteristics of biodiesel fuel spray using a common rail injection system for direct injection (D.I.) diesel engine was investigated. Experiments were carried out in a constant volume vessel under conditions similar to the real engine condition using a single hole nozzle. Biodiesel fuels from two sources namely; palm oil (BDFp) and cooked oil (BDFc) with the commercial JIS#2diesel fuel were utilized in this research. The OH chemiluminescence technique was used to determine the ignition and the lift-off length of the combusting flame. The natural luminosity technique was applied to study the flame development and the two color pyrometry was applied for the soot formation processes. Ignition delay decreased as the injection pressure progressed from 100 to 300MPa. This was as a result of the enhanced mixing achieved at higher injection pressures.

The effects of spray/wall interaction on diesel combustion and soot formation in a two-dimensional piston cavity were studied with a high speed color video camera in a constant volume combustion vessel. The two-dimensional piston cavity was applied to generate the impinging spray flame. In the cavity, the flat surface which plays a role as the cylinder head has a 13.5 degree angle with the injector axis and the impinging point was located 30 mm away from the nozzle tip. Three injection pressures of 100, 150, and 200 MPa and a single hole diesel injector (hole diameter: 0.133mm) were selected. The flame structure and combustion process were examined by using the color luminosity images. Two-color pyrometry was used to measure the line-of sight soot temperature and concentration by using the R and B channels of the color images. The soot mass generated by impinging spray flame is higher than that of the free spray flame.

Spray characteristics under very small injection amount injected by the hole-type nozzle for a D.I. Diesel engine were investigated using the spray test rig consisting a high-pressure and high-temperature constant volume vessel with optical accesses and a common rail injection system. The Laser Absorption Scattering (LAS) technique was used to visualize the liquid and vapor phase distributions in the evaporating spray. In the very small injection amount condition of the evaporating and free (no wall impingement) spray, the both spray tip penetration and spray angle are larger than those of the non-evaporating free spray. This tendency contradicts the previous observation of the diesel spray with large injection amount and the quasi steady state momentum theory. In the case of the spray impinging on a 2-dimensional piston cavity wall, the spray tip penetration of the evaporating spray is larger than that of the non-evaporating spray.

Strict regulations on air pollution motivates clean combustion research for fossil fuels. To numerically mimic real gasoline fuel reactivity, surrogates are proposed to facilitate advanced engine design and predict emissions by chemical kinetic modelling. However, chemical kinetic models could not accurately predict non-regular emissions, e.g. aldehydes, ketones and unsaturated hydrocarbons, which are important air pollutants. In this work, we propose to use machine-learning algorithms to achieve better predictions. Combustion chemistry of fuels constituting of 10 neat fuels, 6 primary reference fuels (PRF) and 6 FGX surrogates were tested in a jet stirred reactor. Experimental data were collected in the same setup to maintain data uniformity and consistency under following conditions: residence time at 1.0 second, fuel concentration at 0.25%, equivalence ratio at 1.0, and temperature range from 750 to 1100K.

Fuel spray impingement on the combustion chamber wall cannot be avoid in direct injection gasoline engines, resulting in insufficient combustion and unburned hydrocarbon/soot emissions from the engines. And the microscopic characteristics of the impinging spray have a close relation with the fuel film formation, which has a direct effect on the engine performance and emissions. Therefore, figuring out the droplet behaviors of the impinging spray is significantly important for improving the engine performance and reducing emissions. However, the microscopic characteristics of the impinging spray have not been deeply understood and the differences between the impinging and free spray are seldom mentioned in previous study. Therefore, particle image analysis (PIA) technique was applied to detect the microscopic characteristics at the capture location in order to track the droplet behaviors of the spray tip during the propagation process.

The development of highly boosted and high compression spark-ignition engines with enhanced thermal efficiencies is primarily limited by knock and super-knock. Super-knock is an excessively high intensity knock which has been related to a developing detonation process. This study investigates the knocking tendency of different gasoline surrogate fuels with varying research octane numbers (RON), octane sensitivity (S) and composition. The ξ/ɛ diagram with an enclosed detonation peninsula is used to assess the knocking tendency of different fuels. The diagram plots ξ, the ratio of acoustic to auto-ignitive velocity, against ɛ, the ratio of the transit time of an acoustic wave through a hot spot, to the heat release time (τe). Constant volume simulations of auto-ignition delay times (τi) and excitation times (τe) obtained from chemical kinetic calculations, enable calculations of ξ and ɛ.

This research evaluates the capability of data-science models to classify the combustion events in Cooperative Fuel Research Engine (CFR) operated under Homogeneous Charge Compression Ignition (HCCI) conditions. A total of 10,395 experimental data from the CFR engine at the University of Michigan (UM), operated under different input conditions for 15 different fuel blends, were utilized for the study. The combustion events happening under HCCI conditions in the CFR engine are classified into four different modes depending on the combustion phasing and cyclic variability (COVimep). The classes are; no ignition/high COVimep, operable combustion, high MPRR, and early CA50. Two machine learning (ML) models, K-nearest neighbors (KNN) and Support Vector Machines (SVM), are compared for their classification capabilities of combustion events. Seven conditions are used as the input features for the ML models viz.

Owing to the small size of engines and high injection pressures, it is difficult to avoid the fuel spray impingement on the combustion cylinder wall and piston head in Direct Injection Spark Ignition (DISI) engine, which is a possible source of hydrocarbons and soot emission. As a result, the droplets size and distribution are significantly important to evaluate the atomization and predict the impingement behaviors, such as stick, spread or splash. However, the microscopic behaviors of droplets are seldom reported due to the high density of small droplets, especially under high pressure conditions. In order to solve this problem, a “spray slicer” was designed to cut the spray before impingement as a sheet one to observe the droplets clearly. The experiment was performed in a constant volume chamber under non-evaporation condition, and a mini-sac injector with single hole was used.

Pre-chamber ignition systems are considered as an effective technique to achieve an ultra-lean burn combustion. Hot combustion products and flames generated from pre-chamber combustion create high-speed turbulent jets, which ignite an ultra-lean mixture in the main chamber. This turbulent ignition can be classified as a jet and flame ignition process with thermal and chemical kinetic effects imposed on the main chamber by the pre-chamber. The purpose of this paper is to investigate the chemical effects of pre-chamber combustion products on main chamber ignition performance over a range of operating conditions in pre-chamber. A zero-dimensional pre-chamber combustion model was developed using CHEMKIN-PRO software. By varying the equivalence ratio of reactants, simulation results indicated that the pre-chamber generated more active radicals when burning around stoichiometric conditions but more low-carbon species when burning in rich conditions.

A computational fluid dynamics (CFD) guided design optimization was conducted for the piston bowl geometry for a heavy-duty diesel engine. The optimization goal was to minimize engine-out NOx emissions without sacrificing engine peak power and thermal efficiency. The CFD model was validated with experiments and the combustion system optimization was conducted under three selected operating conditions representing low speed, maximum torque, and rated power. A hundred piston bowl shapes were generated, of which 32 shapes with 3 spray angles for each shape were numerically analyzed and one optimized design of piston bowl geometry with spray angle was selected. On average, the optimized combustion system decreased nitrogen oxide (NOx) emissions by 17% and soot emissions by 41% without compromising maximum engine power and fuel economy.

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.

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).

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.

The importance of radiative heat transfer on the combustion and soot formation characteristics under nominal ECN Spray A conditions has been studied numerically. The liquid n-dodecane fuel is injected with 1500 bar fuel pressure into the constant volume chamber at different ambient conditions. Radiation from both gas-phase as well as soot particles has been included and assumed as gray. Three different solvers for the radiative transfer equation have been employed: the discrete ordinate method, the spherical-harmonics method and the optically thin assumption. The radiation models have been coupled with the transported probability density function method for turbulent reactive flows and soot, where unresolved turbulent fluctuations in temperature and composition are included and therefore capturing turbulence-chemistry-soot-radiation interactions. Results show that the gas-phase (mostly CO2 ad H2O species) has a higher contribution to the net radiation heat transfer compared to soot.

The tiny and normal injection quantity instances usually happen under the multi-injection strategy condition to restrain the uncontrollability of the ignition timing of the homogeneous charge compression ignition (HCCI) combustion concept. Meanwhile, instead of the traditional and fundamental single-hole diesel injector, the axisymmetric multi-hole injectors are usually applied to couple with the combustion chamber under most practical operating conditions. In the current paper, the internal flow and spray characteristics generated by single-hole and multi-hole (10 holes) nozzles under normal (2 mm3/hole) and tiny (0.3 mm3/hole) injection quantity conditions were investigated in conjunction with a series of experimental and computational methods. High-speed video observation was conducted at 10000 and 100000 fps under the condition of 120 MPa rail pressure, 1.5 MPa ambient pressure, room temperature, and nitrogen environment to visualize different spray properties.

Achieving robust ignitability for compression ignition of diesel engines at cold conditions is traditionally challenging due to insufficient fuel vaporization, heavy wall impingement, and thick wall films. Gasoline compression ignition (GCI) has shown the potential to offer an enhanced NOx-particulate matter tradeoff with diesel-like fuel efficiency, but it is unknown how the volatility and reactivity of the fuel will affect ignition under very cold conditions. Therefore, it is important to investigate the impact of fuel physical and chemical properties on ignition under pressures and temperatures relevant to practical engine operating conditions during cold weather. In this paper, 0-D and 3-D computational fluid dynamics (CFD) simulations of GCI combustion at cold conditions were performed.

Over the years, spark-ignition engine operation has changed significantly, driven by many factors including changes in operating conditions. The variation in operating conditions impacts the state of the end-gas, and therefore, its auto-ignition. This can be quantified in terms of K-factor, which weighs the relative contribution of Research Octane Number (RON) and Motor Octane Number (MON) to knocking tendency at any operating condition. The current study investigates the fuel requirements when operating an engine at increasing intake air pressures. A model engine was operated at varying intake air pressure in GT-Power software, from naturally aspirated intake air to heavily boosted intake air pressure of 4 bar absolute. The pressure-temperature information from the GT-Power model was used to calculate ignition delay times of the unburnt end-gas composed of a sensitive and a non-sensitive fuel in ChemKin software.

The concept of two closely spaced micro-orifices (group hole nozzle) has been studied as a promising technology for the reduction of soot emission from direct injection (DI) diesel engines by improving the fuel atomization and evaporation. One of the main issues on group hole nozzle is the arrangement of orifices with various distances and angles. In this study, the ignition and combustion characteristics of wall-impinging diesel sprays from group-hole nozzles were investigated with various angles between two micro-orifices (included angles). A laser absorption scattering (LAS) technique for non-axisymmetric sprays, developed based on a LAS technique for axisymmetric spray, was applied to investigate the liquid/vapor mass distribution of wall-impinging sprays. The direct flame images and OH radical images inside a high pressure constant volume vessel were captured to analyze the effect of included angle on spray ignition and combustion characteristics.

The objective of the paper is to characterize the diesel spray under the ambient conditions relevant for direct injection (D.I.) diesel engines. The particular emphasis is on the comparisons between laser measurements and predictions by empirical correlations and theoretical analyses. The ultraviolet-visible laser absorption-scattering (LAS) imaging technique is employed to quantitively determine the spray/mixture properties of the diesel spray injected by a hole-type injector, in terms of spray tip penetration and spatial concentration distributions of liquid and vapor phase. The structure of evaporating spray is obtained and analyzed. Based on the penetration correlations in the literature, a non-dimensional analysis of the spray tip penetration data is carried out. The results indicate that a self-similar state of the evaporating fuel spray is achieved.