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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).

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI and RCCI for gasoline light duty engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. This should be co-optimized with appropriate fuel formulations that can autoignite at such temperatures. CFD combustion modeling is used to model the auto ignition of gasoline fuel under compression ignition conditions. Using the fully detailed fuel mechanism consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the real fuel is represented by few major components of create a surrogate fuel mechanism. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode.

This work explores pathways to achieve diesel-like, high-efficiency combustion with stoichiometric 3-way catalyst compatible spark ignition (SI). A high stroke-to-bore engine design (1.5:1) with cooled exhaust gas recirculation (EGR) and high compression ratio (rc) was used to improve engine efficiency by up to 30% compared with a production turbocharged gasoline direct injection spark ignition engine. To achieve efficiency improvements, engine experiments were coupled with computational fluid dynamics simulations to guide and explain experimental trends between the original engine and the high stroke-to-bore ratio design (1.5:1). The effects of EGR and late intake valve closing (IVC) and fuel characteristics are investigated through their effects on knock mitigation. Direct injection of 91 RON E10 gasoline, 99 RON E0 gasoline, and liquified petroleum gas (i.e., propane/autogas) were evaluated with geometric rc ranging from 13.3:1 to 16.8:1.

A computational study using multi-dimensional CFD modeling was performed to investigate the effects of physical properties on diesel engine combustion characteristics with bio-diesel fuels. Properties of typical bio-diesel fuels that were either calculated or measured are used in the study and the simulation results are compared with those of conventional diesel fuels. The sensitivity of the computational results to individual physical properties is also investigated, and the results provide information about the desirable characteristics of the blended fuels. The properties considered in the study include liquid density, vapor pressure, surface tension, liquid viscosity, liquid thermal conductivity, liquid specific heat, latent heat, vapor specific heat, vapor diffusion coefficient, vapor viscosity and vapor thermal conductivity. The results show significant effects of the fuel physical properties on ignition delay and burning rates at various engine operating conditions.

Reactivity Controlled Compression Ignition (RCCI) is an engine combustion strategy that produces low NO and PM emissions with high thermal efficiency. Previous RCCI research has been investigated in single-cylinder heavy-duty engines. The current study investigates RCCI operation in a light-duty multi-cylinder engine at 3 operating points. These operating points were chosen to cover a range of conditions seen in the US EPA light-duty FTP test. The operating points were chosen by the Ad Hoc working group to simulate operation in the FTP test. The fueling strategy for the engine experiments consisted of in-cylinder fuel blending using port fuel-injection (PFI) of gasoline and early-cycle, direct-injection (DI) of diesel fuel. At these 3 points, the stock engine configuration is compared to operation with both the original equipment manufacturer (OEM) and custom-machined pistons designed for RCCI operation.

Given the importance of the fuel-injection process on the combustion and emissions performance of gasoline direct injected engines, there has been significant recent interest in understanding the fluid dynamics within the injector, particularly around the needle and through the nozzles. The pressure losses and transients that occur in the flow passages above the needle are also of interest. Simulations of these injectors typically use the nominal design geometry, which does not always match the production geometry. Computed tomography (CT) using x-ray and neutron sources can be used to obtain the real geometry from production injectors, but there are trade-offs in using these techniques. X-ray CT provides high resolution, but cannot penetrate through the thicker parts of the injector. Neutron CT has excellent penetrating power but lower resolution.

Combustion systems with advanced injection strategies have been extensively studied, but there still exists a significant fundamental knowledge gap on fuel spray interactions with the piston surface and chamber walls. This paper is meant to provide detailed data on spray-wall impingement physics and support the spray-wall model development. The experimental work of spray-wall impingement with non-vaporizing spray characterization, was carried out in a high pressure-temperature constant-volume combustion vessel. The simultaneous Mie scattering of liquid spray and schlieren of liquid and vapor spray were carried out. Diesel fuel was injected at a pressure of 1500 bar into ambient gas at a density of 22.8 kg/m3 with isothermal conditions (fuel, ambient, and plate temperatures of 423 K). A Lagrangian-Eulerian modeling approach was employed to characterize the spray-gas and spray-wall interactions in the CONVERGETM framework by means of a Reynolds-Averaged Navier-Stokes (RANS) formulation.

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.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

Transient engine operations are modeled and simulated with a 1-D code (GT Power) using heat release and emission data computed by a 3-D CFD code (Kiva3). During each iteration step of a transient engine simulation, the 1-D code utilizes the 3-D data to interpolate the values for heat release and emissions. The 3-D CFD computations were performed for the compression and combustion stroke of strategically chosen engine operating points considering engine speed, torque and excess air. The 3-D inlet conditions were obtained from the 1-D code, which utilized 3-D heat release data from the previous 1-D unsteady computations. In most cases, only two different sets of 3-D input data are needed to interpolate the transient phase between two engine operating points. This keeps the computation time at a reasonable level. The results are demonstrated on the load response of a generator which is driven by a medium-speed diesel engine.

Accurate individual cylinder Air Fuel Ratio (AFR) feedback provide opportunities for improved engine performance and reduced emissions in spark ignition engines. One potential measurement for individual cylinder AFR is in-cylinder ionization measured by employing the spark plug as a sensor. A number of previous investigations have studied correlations of the ionization signal with AFR and shown promising results. However the studies have typically been limited to single cylinders under restricted operating conditions. This investigation analyzes and characterizes the ionization signals in correlation to individual AFR values obtained from wide-band electrochemical oxygen sensors located in the exhaust runners of each cylinder. Experimental studies for this research were conducted on a 2.0L inline 4 cylinder spark ignited engine with dual independent variable cam phasing and an intake charge motion control valve.

To address the growing need for accurate predictions of combustion phasing and emissions for development of advanced engines, a more accurate definition of model fuels and their associated chemical-kinetics mechanisms are necessary. Wide variations in street fuels require a model-fuel blending methodology to allow simulation of fuel-specific characteristics, such as ignition timing, emissions, and fuel vaporization. We present a surrogate-blending technique that serves as a practical modeling tool for determination of surrogate blends specifically tailored to different real-fuel characteristics, with particular focus on model fuels for gasoline engine simulation. We start from a palette of potential model-fuel components that are based on the characteristic chemical classes present in real fuels. From this palette, components are combined into a surrogate-fuel blend to represent a real fuel with specific fuel properties.

To accurately predict emissions as well as combustion phasing in a homogeneous charge compression ignition (HCCI) engine, detailed chemistry needs to be used in Computational Fluid Dynamics (CFD) modeling. In this work, CFD simulations of an Oak Ridge National Laboratory (ORNL) gasoline HCCI engine have been performed with full coupling to detailed chemistry. Engine experiments using an E30 gasoline surrogate blend were performed at ORNL, which included measurements of several trace species in the exhaust gas. CFD modeling using a detailed mechanism for the same fuel composition used in the experiments was also performed. Comparisons between data and model are made over a range of intake temperatures. The (experiment & model) surrogate blend consists of 33 wt % ethanol, 8.7 % n-heptane and 58.3 % iso-octane. The data and simulations involve timing sweeps using intake temperature to control combustion phasing at a constant fuel rate.

The discrete droplet model is widely used to describe two-phase flows such as high-velocity dense sprays. The interaction between the liquid and the gas phase is modeled via appropriate source terms in the gas phase equations. This approach can lead to a strong dependence of the liquid-gas coupling on the spatial resolution of the gas phase. The liquid-gas coupling requires the computation of source terms using the gas phase properties, and, subsequently, these sources are then distributed onto the gas phase mesh. In this study, a Lagrange polynomial interpolation method has been developed to evaluate the source terms and also to distribute these source terms onto the gas mesh. The focus of this investigation has been on the momentum exchange between the two phases. The Lagrange polynomial interpolation and source term distribution methods are evaluated for non-evaporating sprays using KIVA3 as a modeling platform.

Impingement of jet-to-jet has been found to give improved spray penetration characteristics and higher vaporization rates when compared to multi-hole outwardly injecting fuel injectors which are commonly used in the gasoline engine. The current work studies a non-reacting spray by using a 5-hole impinging-jet style direct-injection injector. The jet-to-jet collision induced by the inwardly opening nozzles of the multi-hole injector produces rapid and short jet breakup which is fundamentally different from how conventional fuel injectors operate. A non-reacting spray study is performed using a 5-hole impinging jet injector and a traditional 6-hole Bosch Hochdruck-Einspritzventil (HDEV)-5 gasoline direct-injection (GDI) injector with gasoline as a fuel injected at 172 bar pressure with ambient temperature of 653 K and 490 K and ambient pressure of 37.4 bar and 12.4 bar.

Dimethyl Ether (DME) is considered a clean alternative fuel to diesel due to its soot-free combustion characteristics and its capability to be produced from renewable energy sources rather than fossil fuels such as coal or petroleum. To mitigate the effect of strong wave dynamics on fuel supply lines caused due to the high compressibility of DME and to overcome its low lubricity, a hydraulically actuated electronic unit injector (HEUI) with pressure intensification was used. The study focuses on high pressure operation, up to 2000 bar, significantly higher than pressure ranges reported previously with DME. A one-dimensional HEUI injector model is built in MATLAB/SIMULINK graphical software environment, to predict the rate of injection (ROI) profile critical to spray and combustion characterization.

Spray structure has a significant effect on emissions and performance of an internal combustion engine. The main objective of this study is to investigate spray structures based on four different multiple jet impingement injectors. These four different multiple jet-to-jet impingement injectors include 1). 4-hole injector (Case 1), which has symmetric inwardly opening nozzles; 2). 5-1-hole (Case 2); 3). 6-2-hole (Case 3); and 4). 7-3-hole (Case 4) which corresponding to 1, 2, 3 numbers of adjacent holes blocked in a 5-hole, 6-hole, and 7-hole symmetrical drill pattern, respectively. All these configurations are basically 4-holes but with different post collision spray structure. Computational Fluid Dynamics (CFD) work of these sprays has been performed using an Eulerian-Lagrangian modelling approach.

Bio-derived fuels are drawing more and more attention in the internal combustion engine (ICE) research field in recent years. Those interests in use of renewable biofuels in ICE applications derive from energy security issues and, more importantly, from environment pollutant emissions concerns. High fidelity numerical study of engine combustion requires advanced computational fluid dynamics (CFD) to be coupled with detailed chemical kinetic models. This task becomes extremely challenging if real fuels are taken into account, as they include a mixture of hundreds of different hydrocarbons, which prohibitively increases computational cost. Therefore, along with employing surrogate fuel models, reduction of detailed kinetic models for multidimensional engine applications is preferred. In the present work, a reduced mechanism was developed for primary reference fuel (PRF) using the directed relation graph (DRG) approach. The mechanism was generated from an existing detailed mechanism.