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Effects of high injection pressure and converging nozzles on combustion and emissions of a multi-cylinder diesel engine were investigated. The engine uses a common-rail injection system that allows a maximum injection pressure of 200 MPa. Various injection pressures were tested to explore the benefits of high injection pressure in achieving low exhaust emissions in diesel engines. Injectors used in this study include conventional straight-hole nozzles and converging nozzles with a K factor of 3. Parametric studies were performed including variations in injection timings, number of injection pulses and EGR levels. It was found that low temperature combustion can be achieved by using high EGR with 1) late single injection or 2) double injection with an early pilot and a late main injection. Investigations revealed that high injection pressures significantly reduced soot emissions with an increase in NOx emissions under conventional injection timing ranges.

Numerical models were used to study the effects of dimethyl ether (DME) on the operation of a compression-ignition engine fueled with premixed natural gas. The models used multi-dimensional engine CFD coupled with detailed chemical kinetics. Combustion characteristics of various compositions of the natural gas and DME mixture were simulated. Results showed that combustion phasing, nitrogen oxides emissions, and effects of fuel compositions on engine operating limits were well predicted. Chemical kinetics analysis indicated that ignition was achieved by DME oxidation, which, in turn, induced natural gas combustion. It was found that low temperature heat release became more significant as DME concentration increased. For an appropriate amount of DME in the mixture, the stable engine operating range became narrower as natural gas concentration increased. The model also captured the low temperature combustion features of the present engine with low nitrogen oxides emissions.

Particulate matters, nitrogen oxides, and carbon monoxides emissions from large utility generators using diesel/biodiesel blends were measured. Stack measurements were performed on-site in a number of power plants by following the standard procedure of US EPA. The test engines were chosen to represent typical diesel engines used for electricity generation in the state. Tests were performed using the regular diesel fuel (B0), 10%, 20% and 100% biodiesel blends (B10, B20, B100). Test results showed that particulate matters and carbon monoxides decreased significantly as biodiesel content increases, whereas nitrogen oxides increased. Test results are consistent with other studies using mobile engines in the literature. Note that arbitrary changes in fuel or engine operating conditions are prohibited in power generation industry. Results of this study have been used by the state government to allow the use of biodiesel blends in stationary generators.

The accurate prediction of fuel sprays is critical to engine combustion and emissions simulations. A fine computational mesh is often required to better resolve fuel spray dynamics and vaporization. However, computations with a fine mesh require extensive computer time. This study developed a methodology that uses a locally refined mesh in the spray region. Such adaptive mesh refinement will enable greater resolution of the liquid-gas interaction while incurring only a small increase in the total number of computational cells. The present study uses an h-refinement adaptive method. A face-based approach is used for the inter-level boundary conditions. The prolongation and restriction procedure preserves conservation of properties in performing grid refinement/coarsening. The refinement criterion is based on the mass of spray liquid and fuel vapor in each cell. The efficiency and accuracy of the present adaptive mesh refinement scheme is demonstrated.

The simultaneous reduction of particulate matter (PM) and nitrous oxides (NOx) emissions form diesel exhaust is key to current research activities. Although various technologies have been introduced to reduce emissions from diesel engines, the in-cylinder reduction of PM and NOx due to improved combustion mechanisms will continue to be an important field in research and development of modern diesel engines. Furthermore increasing prices and question over the availability of diesel fuel derived from crude oil has introduced a growing interest. Hence it is most likely that future diesel engines will be operated on pure biodiesel and/or blends of biodiesel and crude oil-based diesel. In this study the performance of different biodiesel blends under low temperature combustion conditions (i.e., high exhaust gas recirculation and advanced fuel injection schemes) was investigated.

Parallel computing schemes were developed to enhance the computational efficiency of engine spray simulations with adaptive mesh refinement (AMR). Spray simulations have been shown to be grid dependent and thus fine mesh is often used to improve solution accuracy. In this study, dynamic mesh refinement adaptive to spray region was developed and parallelized in KIVA-4. The change of cell and node numbers and the local characteristics in the dynamic mesh refinement posed difficulties in developing efficient parallel computing schemes to achieve low communication overhead and good load balance. The present strategy executed AMR on one processor with data scattering among processors following the adaptation, and performed AMR every ten computational timesteps for enhanced parallel performance. The re-initialization was required and performed at the minimized cost.

Particle Swarm and the Genetic Algorithm were coupled to optimize multiple performance metrics for the combustion of neat biodiesel in a turbocharged, four cylinder, John Deere engine operating under constant partial load. The enhanced algorithm was used with five inputs including EGR, injection pressure, and the timing/distribution of fuel between a pilot and main injection. A merit function was defined and used to minimize five output parameters including CO, NOx, PM, HC and fuel consumption simultaneously. The combination of PSO and GA yielded convergence to a Pareto regime without the need for excessive engine runs. Results along the Pareto front illustrate the tradeoff between NOx and particulate matter seen in the literature.

In this study both double and triple injection strategies were used with fuel pressures up to 300 and 250 MPa, respectively. Tests were conducted at medium load conditions with cooled, high-pressure EGR at a ratio of 40% and higher. A four-cylinder production engine, featuring double turbochargers with one variable geometry turbocharger, was tested. The double injection strategy consisted of a 20% close-coupled pilot injection while the triple injection strategy introduced a post injection consisting of 10% the total cycle fuel. Results of this study do not indicate an advantage to extreme fuel pressure. The increased air entrainment reduces soot while increasing the premixed burn heat release, mean cylinder temperature, and NOx. Compared to the double injection scheme, triple injections achieved much lower soot for the same EGR rate with only a small NOx penalty.

Various mixtures of ammonia (NH₃) and dimethyl ether (DME) were tested in a diesel engine to explore the feasibility of using ammonia as an alternative, non-carbon fuel to mitigate greenhouse gas emissions. The original diesel fuel injection system was replaced with a new system for injecting ammonia-DME mixtures into the cylinder directly. The injection pressure was maintained at approximately 206 bar for various fuel mixtures including 100% DME, 60%DME-40%NH₃, and 40%DME-60%NH₃ (by weight). As ammonia content was increased in the fuel mixture, the injection timing needed to be advanced to ensure successful engine operation. It was found that cycle-to-cycle variation increased significantly when 40%DME-60%NH₃ was used. In the meantime, combustion of 40%DME-60%NH₃ exhibited HCCI characteristics as the injection timing ranged from 90 to 340 before top-dead-center (BTDC). Emissions data show that soot emissions remained extremely low for the fuel mixtures tested.

Accurate modeling of evaporating sprays is critical for diesel engine simulations. The standard spray and evaporation models in KIVA-3V tend to under-predict the vapor penetration, especially at high ambient pressure conditions. A sharp decrease of vapor penetration gradient is observed soon after the liquid spray is completely evaporated due to the lack of momentum sources beyond the liquid spray region. In this study, a gas particle model is implemented in KIVA-3V which tracks the momentum sources resulting from the evaporated spray. Lagrangian tracking of imaginary gas particles is considered until the velocity of the gas particle is comparable to that of the gas phase velocity. The gas particle continuously exchanges momentum with the gas phase and as a result the vapor penetrations are improved. The results using the present gas particle model is compared with experimental data over a wide range of ambient conditions and good levels of agreement are observed in vapor penetration.

Numerical simulations were performed to investigate the combustion process in the Premixed Compression Ignition (PCI) regime in a light-duty diesel engine. The CHEMKIN code was implemented into an updated KIVA-3V release 2 code to simulate combustion and emission characteristics using reduced chemistry. The test engine used for validation data was a single cylinder version of a production 1.9L four-cylinder HSDI diesel engine. The engine operating condition considered was 2,000 rev/min and 5 bar BMEP load. Because high EGR levels are required for combustion retardation to make PCI combustion possible, the EGR rate was set at a relatively high level (40%) and injection timing sweeps were considered. Since injection timings were very advanced, impingement of the fuel spray on the piston bowl wall was unavoidable. To model the effects of fuel films on exhaust emissions, a drop and wall interaction model was implemented in the present code.

The objective of this work was to identify methods of reliably predicting optimum operating conditions in an experimental compression ignition engine using multiple injections. Abstract modeling offered an efficient way to predict large volumes data, when compared with simulation, although the initial cost of constructing such models can be large. This work aims to reduce that initial cost by adding knowledge about the favorable network structures and training rules which are discovered. The data were gathered from a high pressure common rail direct injection turbocharged compression ignition engine utilizing a high EGR configuration. The range of design parameters were relatively large; 100 MPa - 240 MPa for fuel pressure, up to 62% EGR using a modified, long-route, low pressure EGR system, while the pilot timing, main timing, and pilot ratio were free within the safe operating window for the engine.

Accelerated computational optimization of a diesel engine calibration was achieved by combining Support Vector Regression models with the Particle Swarm Optimization routine. The framework utilized a full engine simulation as a surrogate for a real engine test with test parameters closely resembling a typical 4.5L diesel engine. Initial tests were run with multi-modal test problems including Rastragin's, Bukin's, Ackely's, and Schubert's functions which informed the ML model tuning hyper-parameters. To improve the performance of the engine the hybrid approach was used to optimize the Fuel Pressure, Injection Timing, Pilot Timing and Fraction, and EGR rate. Nitrogen Oxides, Particulate Matter, and Specific Fuel Consumption are simultaneously reduced. As expected, optimums reflect a late injection strategy with moderately high EGR rates.

The impact of fuel droplets on heated surfaces is of great importance in internal combustion engines. In engine computational fluid dynamics (CFD) simulations, the drop-wall interaction is usually considered by using models derived from experimental data and correlations rather than direct simulations. This paper presented a numerical method based on smoothed particle hydrodynamics (SPH), which can directly simulate the impact process of fuel droplets impinging on solid surfaces. The SPH method is a Lagrangian meshfree particle method. It discretizes fluid into a number of SPH particles and governing equations of fluid into a set of particle equations. By solving the particle equations, the movement of particles can be obtained, which represents the fluid flows. The SPH method is able to simulate the large deformation and breakup of liquid drops without using additional interface tracking techniques.

Understanding the fundamental details of drop/wall interactions is important to improving engine performance. Most of the drop-wall interactions studies are based on the impact of a single drop on the wall. To accurately mimic and model the real engine conditions, it is necessary to characterize spray/wall interactions with different impingement frequencies at a wide range of wall temperatures. In this study, a numerical method, based on Smoothed Particle Hydrodynamics (SPH), is used to simulate consecutive droplet impacts on a heated wall both below and above the Leidenfrost temperature. Impact regimes are identified for various impact conditions by analyzing the time evolution of the post-impingement process of n-heptane drops at different impingement frequencies and wall surface temperatures. For wall temperature below the Leidenfrost temperature, the recoiled film does not leave the surface.