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Premixed Charge Compression Ignition (PCCI), a Low Temperature Combustion (LTC) strategy for diesel engines is of increasing interest due to its potential to simultaneously reduce soot and NOx emissions. However, the influence of mixture preparation on combustion phasing and heat release rate in LTC is not fully understood. In the present study, the influence of injection timing on mixture preparation, combustion and emissions in PCCI mode is investigated by experimental and computational methods. A sequential coupling approach of 3D CFD with a Stochastic Reactor Model (SRM) is used to simulate the PCCI engine. The SRM accounts for detailed chemical kinetics, convective heat transfer and turbulent micro-mixing. In this integrated approach, the temperature-equivalence ratio statistics obtained using KIVA 3V are mapped onto the stochastic particle ensemble used in the SRM.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

This paper first summarizes a new theoretical description that quantifies the effects of real-fluid thermodynamics on liquid fuel injection processes as a function of pressure at typical engine operating conditions. It then focuses on the implications this has on modeling such flows with emphasis on application of the Large Eddy Simulation (LES) technique. The theory explains and quantifies the major differences that occur in the jet dynamics compared to that described by classical spray theory in a manner consistent with experimental observations. In particular, the classical view of spray atomization as an appropriate model at some engine operating conditions is questionable. Instead, non-ideal real-fluid behavior must be taken into account using a multicomponent formulation that applies to hydrocarbon mixtures at high-pressure supercritical conditions.

A detailed understanding of the various factors affecting the trends in gross-indicated thermal efficiency with changes in key operating parameters has been carried out, applied to a one-liter displacement single-cylinder boosted Low-Temperature Gasoline Combustion (LTGC) engine. This work systematically investigates how the supplied fuel energy splits into the following four energy pathways: gross-indicated thermal efficiency, combustion inefficiency, heat transfer and exhaust losses, and how this split changes with operating conditions. Additional analysis is performed to determine the influence of variations in the ratio of specific heat capacities (γ) and the effective expansion ratio, related to the combustion-phasing retard (CA50), on the energy split. Heat transfer and exhaust losses are computed using multiple standard cycle analysis techniques. The various methods are evaluated in order to validate the trends.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

Developing an improved understanding of transient mixing and combustion processes inherent in diesel injection is an important element in the design of advanced engines. This paper provides a detailed analysis of these processes using an idealized benchmark configuration designed to facilitate precise comparisons between different models and numerical methods. The computational domain is similar to the Engine Combustion Network (www.sandia.gov/ECN) Spray-A injector with n-dodecane as the fuel. Quantified idealizations are made in the treatment of boundary conditions to eliminate ambiguities and unknowns associated with the actual injector(s) used in the experiment. These ambiguities hinder comparisons aimed at understanding the accuracy of different models and the coupled effects of potential numerical errors.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

Minimizing heat-transfer (HT) losses is important for both improving engine efficiency and increasing exhaust energy for turbocharging and exhaust aftertreatment management, but engine combustion system design to minimize these losses is hindered by significant uncertainties in prediction. Empirical HT correlations such as the popular Woschni model have been developed and various attempts at improving predictions have been proposed since the 1960s, but due to variations in facilities and techniques among various studies, comparison and assessment of modelling approaches among multiple combustion modes is not straightforward. In this work, simultaneous cylinder-wall temperature and OH* chemiluminescence high-speed video are all recorded in a single heavy-duty optical engine operated under multiple combustion modes. OH* chemiluminescence images provide additional insights for identifying the causes of near-wall heat flux changes.

This paper1 explores some of the important considerations in devising a practical and consistent framework and methodology for working with experiments and experimental data in connection with modeling and prediction. The paper outlines a pragmatic and versatile “real-space” approach within which experimental and modeling uncertainties (correlated and uncorrelated, systematic and random, aleatory and epistemic) are treated to mitigate risk in modeling and prediction. The elements of data conditioning, model conditioning, model validation, hierarchical modeling, and extrapolative prediction under uncertainty are examined. An appreciation can be gained for the constraints and difficulties at play in devising a viable end-to-end methodology. The considerations and options are many, and a large variety of viewpoints and precedents exist in the literature, as surveyed here. Rationale is given for the various choices taken in assembling the novel real-space end-to-end framework.

Single-cylinder engine experiments were used to investigate a fuel reactivity controlled compression ignition (RCCI) concept in both light- and heavy-duty engines and comparisons were made between the two engine classes. It was found that with only small changes in the injection parameters, the combustion characteristics of the heavy-duty engine could be adequately reproduced in the light-duty engine. Comparisons of the emissions and performance showed that both engines can simultaneously achieve NOx below 0.05 g/kW-hr, soot below 0.01 g/kW-hr, ringing intensity below 4 MW/m2, and gross indicated efficiencies above 50 per cent. However, it was found that the peak gross indicated efficiency of the baseline light-duty engine was approximately 7 per cent lower than the heavy-duty engine. The energy balances of the two engines were compared and it was found that the largest factor contributing to the lower efficiency of the light-duty engine was increased heat transfer losses.

This study systematically investigates the effects of various engine operating parameters on the thermal efficiency of a boosted HCCI engine, and the potential of E10 to extend the high-load limit beyond that obtained with conventional gasoline. Understanding how these parameters can be adjusted and the trade-offs involved is critical for optimizing engine operation and for determining the highest efficiencies for a given engine geometry. Data were acquired in a 0.98 liter, single-cylinder HCCI research engine with a compression-ratio of 14:1, and the engine facility was configured to allow precise control over the relevant operating parameters. The study focuses on boosted operation with intake pressures (Pin) ≥ 2 bar, but some data for Pin < 2 bar are also presented. Two fuels are considered: 1) an 87-octane gasoline, and 2) E10 (10% ethanol in this same gasoline) which has a lower autoignition reactivity for boosted operation.

A single-cylinder light-duty diesel engine was used to investigate dual fuel reactivity controlled compression ignition (RCCI) operated with two different fuel combinations: gasoline/diesel fuel and methanol/diesel fuel. The engine was operated over a range of conditions, from 1500 to 2300 rpm and 3.5 to 17 bar gross IMEP. Using the stock re-entrant piston bowl geometry, both fuel combinations were able to achieve low NOx and PM emissions with a peak gross indicated efficiency of 48%. However, at light load conditions both gasoline and methanol yielded poorer combustion efficiencies. Previous studies have shown that the high-levels of piston induced mixing that are created by the stock piston are not required, and in fact are detrimental due to increased heat transfer losses, for premixed combustion. Thus a modified piston featuring a shallow, flat piston bowl with nearly no squish land was also investigated.

This paper presents a study of the turbulence field in an optical diesel engine operated under motored conditions using both large eddy simulation (LES) and Particle Image Velocimetry (PIV). The study was performed in a laboratory optical diesel engine based on a recent production engine from VOLVO Car. PIV is used to study the flow field in the cylinder, particularly inside the piston bowl that is also optical accessible. LES is used to investigate in detail the structure of the turbulence, the vortex cores, and the temperature field in the entire engine, all within a single engine cycle. The LES results are compared with the PIV measurements in a 40 × 28 mm domain ranging from the nozzle tip to the cylinder wall. The LES grid consists of 1283 cells. The grid dynamically adjusts itself as the piston moves in the cylinder so that the engine cylinder, including the piston bowl, is described by the grid.

Numerical models are used in this study to investigate the oil flow and heat transfer in the piston gallery of a diesel engine. An experiment is set up to validate the numerical models. In the experiment a fixed, but adjustable steel plate is instrumented and pre-heated to a certain temperature. The oil is injected vertically upwards from an underneath injector and impinges on the bottom of the plate. The reduction of the plate temperature is recorded by the thermocouples pre-mounted in the plate. The numerical models are used to predict the temperature history at the thermocouple locations and validated with the experimental data. After the rig model validation, the numerical models are applied to evaluate the oil sloshing and heat transfer in the piston gallery. The piston motion is modeled by a dynamic mesh model, and the oil sloshing is modeled by the VOF (volume of fluid) multiphase model.

Engine combustion strategies that preserve high cycle efficiency while minimizing engine-out pollutant emissions are the focus of major research efforts around the world. Such high efficiency clean combustion (HECC) strategies typically employ compression ignition of a charge that exhibits an elevated degree of fuel/air premixing and/or dilution with combustion products. Prior studies have shown that a highly dilute, mixing-controlled combustion strategy using a high-cetane, oxygenated fuel can achieve HECC while avoiding the control, high-load knock, and light-load incomplete combustion difficulties that are often experienced with approaches that use a high degree of charge premixing. On the other hand, employing high dilution levels (e.g., by using large amounts of cooled exhaust gas recirculation, EGR) can place excessive burdens on engine heat exchangers and air-handling systems.

A 2-D CFD model was developed to describe the heat transfer, and reaction kinetics in a honeycomb structured ceramic diesel particulate trap. This model describes the steady state as well as the transient behavior of the flow and heat transfer during the trap regeneration processes. The trap temperature profile was determined by numerically solving the 2-D unsteady energy equation including the convective, heat conduction and viscous dissipation terms. The convective terms were based on a 2-D analytical flow field solution derived from the conservation of mass and momentum equations (Opris, 1997). The reaction kinetics were described using a discretized first order Arrhenius function. The 2-D term describing the reaction kinetics and particulate matter conservation of mass was added to the energy equation as a source term in order to represent the particulate matter oxidation. The filtration model describes the particulate matter accumulation in the trap.

This study focuses on how to predict hot spots of one of the cylinders of a V8 5.4 L FORD engine running at full load. The KIVA code with conjugate heat transfer capability to simulate the fast transient heat transfer process between the gas and the solid phases has been developed at the Michigan Technological University and will be used in this study. Liquid coolant flow was simulated using FLUENT and will be used as a boundary condition to account for the heat loss to the cooling fluid. In the first step of calculation, the coupling between the gas and the solid phases will be solved using the KIVA code. A 3D transient wall heat flux at the gas-solid interface is then compiled and used along with the heat loss information from the FLUENT data to obtain the temperature distribution for the engine metal components, such as cylinder wall, cylinder head, etc.

One-dimensional single-zone and two-zone analyses have been exercised to calculate the mass fraction burned in an engine operating on ethanol/gasoline-blended fuels using the cylinder pressure and volume data. The analyses include heat transfer and crevice volume effects on the calculated mass fraction burned. A comparison between the two methods is performed starting from the derivation of conservation of energy and the method to solve the mass fraction burned rates through the results including detailed explanation of the observed differences and trends. The apparent heat release method is used as a point of reference in the comparison process. Both models are solved using the LU matrix factorization and first-order Euler integration.

As the incentive to produce cleaner and more efficient engines increases, diesel engines will become a primary, worldwide solution. Producing diesel engines with higher efficiency and lower emissions requires a fundamental understanding of the interaction of the injected fuel with air as well as with the surfaces inside the combustion chamber. One aspect of this interaction is spray impingement on the piston surface. Impingement on the piston can lead to decreased combustion efficiency, higher emissions, and piston damage due to thermal loading. Modern high-speed diesel engines utilize high pressure common-rail direct-injection systems to primarily improve efficiency and reduce emissions. However, the high injection pressures of these systems increase the likelihood that the injected fuel will impinge on the surface of the piston.

The objective of this investigation is to optimize a light-duty diesel engine in order to minimize soot, NOx, carbon monoxide (CO), unburned hydrocarbon (UHC) emissions and peak pressure rise rate (PPRR) while improving fuel economy in a low oxygen environment. Variables considered are the injection timings, fractional amount of fuel per injection, half included spray angle, swirl, and stepped-bowl piston geometry. The KIVA-CHEMKIN code, a multi-dimensional computational fluid dynamics (CFD) program with detailed chemistry is used and is coupled to a multi-objective genetic algorithm (MOGA) along with an automated grid generator. The stepped-piston bowl allows more options for spray targeting and improved charge preparation. Results show that optimal combinations of the above variables exist to simultaneously reduce emissions and fuel consumption. Details of the spray targeting were found to have a major impact on the combustion process.