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A zero-dimension model of spray development and particulate emissions for direct-injection combustion was developed. The model describes the major characteristics of the injection plume including: spray angle, liquid penetration, lift-off length, and temperatures of regions within the spray. The model also predicts particulate mass output over a span of combustion cycles, as well as a particulate mass-history over a single combustion event. The model was developed by applying established conceptual models for direct injection combustion to numerical relations, to develop a mathematical description of events. The model was developed in a Matlab Simulink environment to promote modularity and ease of use.

A detailed thermodynamic analysis was performed to demonstrate the fundamental efficiency advantage of an opposed-piston two-stroke engine over a standard four-stroke engine. Three engine configurations were considered: a baseline six-cylinder four-stroke engine, a hypothetical three-cylinder opposed-piston four-stroke engine, and a three-cylinder opposed-piston two-stroke engine. The bore and stroke per piston were held constant for all engine configurations to minimize any potential differences in friction. The closed-cycle performance of the engine configurations were compared using a custom analysis tool that allowed the sources of thermal efficiency differences to be identified and quantified.

This research focused on the effects of split injection on combustion in a diesel environment. It was done in a specially designed engine-fed combustion chamber (swirl ratio of 5) with full field optical access through a quartz window. The simulated engine combustion chamber used a special backwards spraying injector (105°). The electronically controlled injector could control the size and position of it's, two injections. Both injections were through the same nozzle and it produced very rapid injections (1.5 ms) with a maximum injection pressure of 130 MPa. Experimental data included: rate of injection, injector pressure, combustion chamber dumping (NO & NOx concentrations), flame temperature, KL factor (soot concentration) combustion pressure, and rate of pressure rise. Injection rates indicate that the UCORS injection system creates very rapid injections with the ability to produce controllable split injections.

This research focused on the effects of split injection on fuel spray behavior in a diesel environment. It was done in a special designed engine-fed combustion chamber (swirl ratio of 5) with full field optical access through a quartz window. The simulated engine combustion chamber used a special backwards spraying injector (105°). The electronically controlled injector could control the size and position of it's two injections. Both injections were through the same nozzle and it produced very rapid injections (1.5 ms) with a maximum injection pressure of 130 MPa. Experimental data included: rate of injection, injector pressure, spray plume images, tip penetration, liquid and vapor fuel distributions, combustion pressure, and rate of pressure rise. From 105° forward scatter images, tip penetration was observed to be very rapid and reached a plateau at 25 mm.

To date there is no universal agreement as to the interaction between fuel type, fuel-air mixture preparation and combustion chamber flow characteristics and their effect on soot formation. A propane fueled modified conical back-mixed steady flow reactor was built in which the fuel and air could be mixed together in varying degrees and reacted in at different mixing intensities. The onset of soot and soot loading were determined qualitatively by a photomultiplier focused on the volume inside the reactor. Increasing the degree of premix from a diffusion flame to a distribution of Φmax/Φavg = 5.0 resulted in increases of 3 to 17 percent of the soot-onset equivalence ratio and decreases in soot loading down to zero. Changes in the mixing intensity from 32.5 sec−1 to 75.7 sec−1 resulted in a change in the soot-onset equivalence ratio from 1.26 to 1.52. Soot loading was found to depend on both the mixing intensity, β, and the average number of mixes per mean residence time, β/α.

In this paper, effect of intake air temperature, coolant temperature, and compression ratio on start of heat release (SOHR) in HCCI engines is investigated. The operational range with HCCI operation was determined experimentally using a CFR (Cooperative Fuels Research) engine with n-butane as the fuel. In-cylinder pressure was processed to evaluate SOHR. The effect of intake air and coolant temperature on SOHR increases as engine speed increases. In order to gain more insight into the combustion phenomena, SOHR was calculated using the theory of Livengood-Wu and compared with the experimental data. Dependence of SOHR on the equivalence ratio shows good correspondence between experiment and calculation. On the contrary, dependence on the intake air temperature and compression ratio shows poorer correspondence with predictions, especially under low engine speed. We interpret this as an indication of the importance of the active intermediate species that remain in the combustion chamber.

A single cylinder, Cummins NH, direct-injection, diesel engine has been operated in order to evaluate the effects of aromatic content and aromatic structure on diesel engine particulates. Results from three fuels are shown. The first fuel, a low sulfur Chevron diesel fuel was used as a base fuel for comparison. The other fuels consisted of the base fuel and 10% by volume of 1-2-3-4 tetrahydronaphthalene (tetralin) a single-ring aromatic and naphthalene, a double-ring aromatic. The fuels were chosen to vary aromatic content and structure while minimizing differences in boiling points and cetane number. Measurements included exhaust particulates using a mini-dilution tunnel, exhaust emissions including THC, CO2, NO/NOx, O2, injection timing, two-color radiation, soluble organic fraction, and cylinder pressure. Particulate measurements were found to be sensitive to temperature and flow conditions in the mini-dilution tunnel and exhaust system.

Sources of unburned hydrocarbon (UHC) emissions are examined for a highly dilute (10% oxygen concentration), moderately boosted (1.5 bar), low load (3.0 bar IMEP) operating condition in a single-cylinder, light-duty, optically accessible diesel engine undergoing partially-premixed low-temperature combustion (LTC). The evolution of the in-cylinder spatial distribution of UHC is observed throughout the combustion event through measurement of liquid fuel distributions via elastic light scattering, vapor and liquid fuel distributions via laser-induced fluorescence, and velocity fields via particle image velocimetry (PIV). The measurements are complemented by and contrasted with the predictions of multi-dimensional simulations employing a realistic, though reduced, chemical mechanism to describe the combustion process.

The objective of this research is a detailed investigation of particulate sizing and number count from a spark-ignited, direct-injection (SIDI) engine at different operating conditions. The engine is a 549 [cc] single-cylinder, four-valve engine with a flat-top piston, fueled by Tier II EEE. A baseline engine operating condition, with a low number of particulates, was established and repeatability at this condition was ascertained. This baseline condition is specified as 2000 rpm, 320 kPa IMEP, 280 [°bTDC] end of injection (EOI), and 25 [°bTDC] ignition timing. The particle size distributions were recorded for particle sizes between 7 and 289 [nm]. The baseline particle size distribution was relatively flat, around 1E6 [dN/dlogDp], for particle diameters between 7 and 100 [nm], before dropping off to decreasing numbers at larger diameters. Distributions resulting from a matrix of different engine conditions were recorded.

Premixed diesel combustion offers the potential of high thermal efficiency and low emissions, however, because the rapid rate of pressure rise and short combustion durations are often associated with low temperature combustion processes, noise is also an issue. The reduction of combustion noise is a technical matter that needs separate attention. Engine noise research has been conducted experimentally with a premixed diesel engine and techniques for engine noise simulation have been developed. The engine employed in the research here is a supercharged, single cylinder DI diesel research engine with a high pressure common rail fuel injection system. In the experiments, the engine was operated at 1600 rpm and 2000 rpm, the engine noise was sampled by two microphones, and the sampled engine noise was averaged and analyzed by an FFT sound analyzer.

Neural networks are useful tools for optimization studies since they are very fast, so that while capturing the accuracy of multi-dimensional CFD calculations or experimental data, they can be run numerous times as required by many optimization techniques. This paper describes how a set of neural networks trained on a multi-dimensional CFD code to predict pressure, temperature, heat flux, torque and emissions, have been used by a genetic algorithm in combination with a hill-climbing type algorithm to optimize operating parameters of a diesel engine over the entire speed-torque map of the engine. The optimized parameters are mass of fuel injected per cycle, shape of the injection profile for dual split injection, start of injection, EGR level and boost pressure. These have been optimized for minimum emissions. Another set of neural networks have been trained to predict the optimized parameters, based on the speed-torque point of the engine.

In-cylinder measurements of soot particle size, number density, and temperature have been made using optical measurements in a direct injection diesel engine. The measurements were made at one location approximately 5 mm long and 1.5 mm wide above the bowl near the head. Two optical techniques were used simultaneously involving light scattering, extinction and radiation. An optical probe was designed and mounted in a modified exhaust valve which introduced a beam of light into the cylinder and collected the scattered and radiating light from the soot. The resulting measurements were semi-quantitative, giving an absolute uncertainty on the order of ± 50% which was attributed mainly to the uncertainty of the optical properties of the soot and the heterogeneous nature of the soot cloud. Measurements at three speeds and three overall equivalence ratios were made.

Numerical simulations are performed to investigate the fuel/air mixing preparation in a gasoline direct injection (GDI) engine. A two-valve OHV engine with wedge combustion chamber is investigated since automobiles equipped with this type of engine are readily available in the U.S. market. Modifying and retrofitting these engines for GDI operation could become a viable scenario for some engine manufactures. A pressure-swirl injector and wide spacing injection layout are adapted to enhance mixture preparation. The primary interest is on preparing the mixture with adequate equivalence ratio at the spark plug under a wide range of engine operating conditions. Two different engine operating conditions are investigated with respect to engine speed and load. A modified version of the KIVA-3V multi-dimensional CFD code is used. The modified code includes the Linearized Instability Sheet Atomization (LISA) model to simulate the development of the hollow cone spray.

A cylinder model was developed using artificial neural networks (ANN). The cylinder model utilized the trained ANN models to predict engine parameters including cylinder pressures, cylinder temperatures, cylinder wall heat transfer, NOx and soot emissions. The ANN models were trained to approximate CFD simulation results of an engine. The ANN cylinder model was then applied to predict engine performance and emissions over the standard heavy-duty FTP transient cycle. The engine responses varying over the engine speed and torque range were simulated in the course of the transient test cycle. It was demonstrated that the ANN cylinder model is capable of simulating the characteristics of the engine operating under transient conditions reasonably well.

The objective of this research is a detailed investigation of multiple injections in a highly-dilute diesel low temperature combustion (LTC) regime. This research concentrates on understanding the performance and emissions benefits of multiple injections via experiments and simulations in a 0.48L signal cylinder light-duty engine operating at 2000 r/min and 5.5 bar IMEP. Controlled experiments in the single-cylinder engine are then combined with three computational tools, namely heat release analysis of measured cylinder pressure, a phenomenological spray model using in-cylinder thermodynamics [1], and KIVA-3V Chemkin CFD computations recently tested at LTC conditions [2]. This study examines the effects of fuel split distribution, injection event timing, rail pressure, and boost pressure which are each explored within a defined operation range in LTC.

To help account for fuel distribution during combustion in diesel engines, a fuel film model has been developed and implemented into the KIVA-II code [1]. Spray-wall interaction and spray-film interaction are also incorporated into the model. Modified wall functions for evaporating, wavy films are developed and tested. The model simulates thin fuel film flow on solid surfaces of arbitrary configuration. This is achieved by solving the continuity, momentum and energy equations for the two dimensional film that flows over a three dimensional surface. The major physical effects considered in the model include mass and momentum contributions to the film due to spray drop impingement, splashing effects, various shear forces, piston acceleration, dynamic pressure effects, and convective heat and mass transfer.

A multidimensional simulation of Auxiliary Gas Injection (AGI) for late cycle oxygen enrichment was exercised to assess the merits of AGI for reducing the emissions of soot from heavy duty diesel engines while not adversely affecting the NOx emissions of the engine. Here, AGI is the controlled enhancement of mixing within the diesel engine combustion chamber by high speed jets of air or another gas. The engine simulated was a Caterpillar 3401 engine. For a particular operating condition of this engine, the simulated soot emissions of the engine were reduced by 80% while not significantly affecting the engine-out NOx emissions compared to the engine operating without AGI. The effects of AGI duration, timing, and orientation are studied to confirm the window of opportunity for realizing lower engine-out soot while not increasing engine out NOx through controlled enhancement of in-cylinder mixing.

Multidimensional computations were carried out to simulate the in-cylinder fuel/air mixing process of a direct-injection spark-ignition engine using a modified version of the KIVA-3 code. A hollow cone spray was modeled using a Lagrangian stochastic approach with an empirical initial atomization treatment which is based on experimental data. Improved Spalding-type evaporation and drag models were used to calculate drop vaporization and drop dynamic drag. Spray/wall impingement hydrodynamics was accounted for by using a phenomenological model. Intake flows were computed using a simple approach in which a prescribed velocity profile is specified at the two intake valve openings. This allowed three intake flow patterns, namely, swirl, tumble and non-tumble, to be considered. It was shown that fuel vaporization was completed at the end of compression stroke with early injection timing under the chosen engine operating conditions.

Artificial neural networks (ANN) have been recognized as universal approximators for nonlinear continuous functions and actively applied in engine research in recent years [1, 2, 3, 4, 5, 6, 7 and 8]. This paper describes the methodology and results of using the ANN to model a turbocharged DI diesel engine. The engine was simulated using the CFD code (KIVA-ERC) over a wide range of operating conditions, and numerical simulation results were used to train the ANN. An efficient data collection methodology using the Design of Experiments (DOE) techniques was developed to select the most characteristic engine operating conditions and hence the most informative data to train the ANN. This approach minimizes the time and cost of collecting training data from either computational or experimental resources. The trained ANN was then used to predict engine parameters such as cylinder pressure, cylinder temperature, NOx and soot emissions, and cylinder heat transfer.

Predictive models of soot formation during Diesel combustion are of great practical interest, particularly in light of newly proposed strict regulations on particulate emissions. A modified version of the phenomenological model of soot formation developed previously has been implemented in KIVA-II CFD code. The model includes major generic processes involved in soot formation during combustion, i.e., formation of soot precursors, formation of surface growth species, soot particle nucleation, coagulation, surface growth and oxidation. The formulation of the model within the KIVA-II is fully coupled with the mass and energy balances in the system. The model performance has been tested by comparison with the results of optical in-cylinder soot measurements in a single cylinder Cummins NH Diesel engine. The predicted soot volume fraction, number density and particle size agree reasonably well with the experimental data.