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A new Computational Fluid Dynamics (CFD) code has been developed in order to overcome the deficiencies of traditional grid generation and mesh motion methods. The new code uses a modified cut-cell Cartesian technique that eliminates the need for the computational grid to coincide with the geometry of interest. The code also includes state-of-the-art numerical techniques and sub-models for simulating the complex physical and chemical processes that occur in engines. Features such as shared and distributed memory parallelization, a multigrid pressure solver and user-specified grid embedding allow for efficient simulations while maintaining the grid resolution necessary for accurate engine modeling. In addition, a new Adaptive Grid Embedding (AGE) technique has been developed and implemented. Sub-models for turbulence, spray injection, spray breakup, liquid drop dynamics, ignition, combustion and emissions are also included in the code.

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

Nowadays Spark Ignition (SI) engine developments focus on downsizing, in order to increase the engine load level and consequently its efficiency. As a side effect, knock occurrence is strongly increased. The current strategy to avoid knock is to reduce the spark advance which limits the potential of downsizing in terms of consumption reduction. Reducing the engine propensity to knock is therefore a first order subject for car manufacturers. Engineers need competitive tools to tackle such a complex phenomenon. In this paper the 3D RANS simulations ability to satisfactorily represent knock tendencies is demonstrated. ECFM (Extended Coherent Flame Model) has been recently implemented by IFPEN in CONVERGE and coupled with TKI (Tabulated Kinetics Ignition) to represent Auto-Ignition in SI engine. These models have been applied on a single cylinder engine configuration dedicated to abnormal combustion study.

The 3-Zones Extended Coherent Flame Model (ECFM3Z) and the Tabulated Kinetics for Ignition (TKI) auto-ignition model are widely used for RANS simulations of reactive flows in Diesel engines. ECFM3Z accounts for the turbulent mixing between one zone that contains compressed air and EGR and another zone that contains evaporated fuel. These zones mix to form a reactive zone where combustion occurs. In this mixing zone TKI is applied to predict the auto-ignition event, including the ignition delay time and the heat release rate. Because it is tabulated, TKI can model complex fuels over a wide range of engine thermodynamic conditions. However, the ECFM3Z/TKI combustion modeling approach requires an efficient predictive spray injection calculation. In a Diesel direct injection engine, the turbulent mixing and spray atomization are mainly driven by the liquid/gas coupling phenomenon that occurs at moving liquid/gas interfaces.

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.

Flow field asymmetry can lead to an asymmetric mixture preparation in Diesel engines. To understand the evolution of this asymmetry, it is necessary to characterize the in-cylinder flow over the full compression stroke. Moreover, since bowl-in-piston cylinder geometries can substantially impact the in-cylinder flow, characterization of these flows requires the use of geometrically correct pistons. In this work, the flow has been visualized via a transparent piston top with a realistic bowl geometry, which causes severe experimental difficulties due to the spatial and temporal variation of the optical distortion. An advanced optical distortion correction method is described to allow reliable particle image velocimetry (PIV) measurements through the full compression stroke. Based on the ensemble-averaged velocity results, flow asymmetry characterized by the swirl center offset and the associated tilting of the vortex axis is quantified.

The primary objective of the research discussed here was to compare the commercial computational fluid dynamics (CFD) software, CONVERGE, and a prevalent open-source code, OpenFOAM, with regard to their ability to predict spray and combustion characteristics. The high-fidelity data were obtained from the Engine Combustion Network (ECN) at Sandia National Laboratory in a constant-volume combustion vessel under well-defined, controlled conditions. The experiments and simulations were performed by using two diesel surrogate fuels (i.e., n-heptane and n-dodecane) under both non-reacting and reacting conditions. Specifically, ECN data on spray penetration, liquid length, vapor penetration, mixture fraction, ignition delay, and flame lift-off length (LOL) were used to validate both codes. Results indicate that both codes can predict the above experimental characteristics very well.

An extensive numerical study of two-phase flow inside the nozzle holes and the issuing jets for a multi-hole direct injection gasoline injector is presented. The injector geometry is representative of the Spray G nozzle, an eight-hole counter-bored injector, from the Engine Combustion Network (ECN). Homogeneous Relaxation Model (HRM) coupled with the mixture multiphase approach in the Eulerian framework has been utilized to capture the phase change phenomena inside the nozzle holes. Our previous studies have demonstrated that this approach is capable of capturing the effect of injection transients and thermodynamic conditions in the combustion chamber, by predicting phenomenon such as flash boiling. However, these simulations were expensive, especially if there is significant interest in predicting the spray behavior as well.

The current trend of downsizing used in gasoline engines, while reducing fuel consumption and CO2 emissions, imposes severe thermal loads inside the combustion chamber. These critical thermodynamic conditions lead to the possible auto-ignition (AI) of fresh gases hot-spots around Top-Dead-Center (TDC). At this very moment where the surface to volume ratio is high, wall heat transfer influences the temperature field inside the combustion chamber. The use of a realistic wall temperature distribution becomes important in the case of a downsized engine where fresh gases hot spots found near high temperature walls can initiate auto-ignition. This paper presents a comprehensive numerical methodology for an accurately prediction of thermodynamic conditions inside the combustion chamber based on Conjugate Heat Transfer (CHT).

Reynolds-averaged Navier-Stokes (RANS) modeling is expected to deliver an ensemble-averaged result for the majority of turbulent flows. This could lead to the conclusion that multi-cycle internal combustion engine (ICE) simulations performed using RANS must exhibit a converging numerical solution after a certain number of consecutive cycles. However, for some engine configurations unsteady RANS simulations are not guaranteed to deliver an ensemble-averaged result. In this paper it is shown that, when using RANS modeling to simulate multiple engine cycles, the cycle-to-cycle variations (CCV) generated from different initial conditions at each cycle are not damped out even after a large number of cycles. A single-cylinder GDI research engine is simulated using RANS modeling and the numerical results for 20 consecutive engine cycles are evaluated for two specific operating conditions.

A, three-dimensional CFD code, based on the KIVA code, is used to explore alternatives to conventional DI diesel engine designs for reducing NOx and soot emissions without sacrificing engine performance. The effects of combustion chamber design and fuel spray orientation are investigated using a new proposed GAMMA engine concept, and two new multiple injector combustion system (MICS) designs which utilize multiple injectors to increase gas motion and enhance fuel/air mixing in the combustion chamber. From these computational studies, it is found that both soot and nitrous oxide emissions can be significantly reduced without the need for more conventional emission control strategies such as EGR or ultra high injection pressure. The results suggest that CFD models can be a useful tool not only for understanding combustion and emissions production, but also for investigating new design concepts.

The recently developed KIVA-GA computer code was used in the current study to optimize the combustion chamber geometry of a heavy -duty diesel truck engine and a high-speed direct-injection (HSDI) small-bore diesel engine. KIVA-GA performs engine simulations within the framework of a genetic algorithm (GA) global optimization code. Design fitness was determined using a modified version of the KIVA-3V code, which calculates the spray, combustion, and emissions formation processes. The measure of design fitness includes NOx, unburned HC, and soot emissions, as well as fuel consumption. The simultaneous minimization of these factors was the ultimate goal. The KIVA-GA methodology was used to optimize the engine performance using nine input variables simultaneously. Three chamber geometry related variables were used along with six other variables, which were thought to have significant interaction with the chamber geometry.

This paper presents on-the-fly chemical mechanism reduction (termed as dynamic mechanism reduction) for speeding up the chemistry solution for practical internal combustion engine simulations. Small mechanisms are built at each time step which are valid under the local conditions of each cell. The Directed Relation Graph with Error Propagation (DRGEP) algorithm is used for generating local skeletal mechanisms. Dynamic mechanism reduction is combined with adaptive zoning (termed as multi-zone) to achieve good computational speed-up for engine simulations. The accuracy and efficiency of dynamic mechanism reduction is evaluated for a wide range of scenarios including (a) Diesel combustion, (b) Homogeneous Charge Compression Ignition (HCCI) combustion, and (c) Dual fuel combustion.

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance.

A set of reduced chemical mechanisms was developed for use in multi-dimensional engine simulations of premixed gasoline combustion. The detailed Primary Reference Fuel (PRF) mechanism (1034 species, 4236 reactions) from Lawrence Livermore National Laboratory (LLNL) was employed as the starting mechanism. The detailed mechanism, referred to here as LLNL-PRF, was reduced using a technique known as Parallel Direct Relation Graph with Error Propagation and Sensitivity Analysis. This technique allows for efficient mechanism reduction by parallelizing the ignition delay calculations used in the reduction process. The reduction was performed for a temperature range of 800 to 1500 K and equivalence ratios of 0.5 to 1.5. The pressure range of interest was 0.75 bar to 40 bar, as dictated by the wide range in spark timing cylinder pressures for the various cases. In order to keep the mechanisms relatively small, two reductions were performed.

Global Sensitivity Analysis (GSA) is conducted for a diesel engine simulation to understand the sensitivities of various modeling constants and boundary conditions in a global manner with regards to multi-target functions such as liquid length, ignition delays, combustion phasing, and emissions. The traditional local sensitivity analysis approach, which involves sequential perturbation of model constants, does not provide a complete picture since all the parameters can be uncertain. However, this approach has been studied extensively and is advantageous from a computational point of view. The GSA simultaneously incorporates the uncertainty information for all the relevant boundary conditions, modeling constants, and other simulation parameters. A global analysis is particularly useful to address the important parameters in a model where the response of the targets to the values of the variables is highly non-linear.

This paper focuses on detailed numerical simulations of direct injection diesel and gasoline sprays from production grade, multi-hole injectors. In a dual-fuel engine the direct injection of both the fuels can facilitate appropriate mixture preparation prior to ignition and combustion. Diesel and gasoline sprays were simulated using high-fidelity Large Eddy Simulations (LES) with the dynamic structure sub-grid scale model. Numerical predictions of liquid penetration, fuel density distribution as well as transverse integrated mass (TIM) at different axial locations versus time were compared against x-ray radiography data obtained from Argonne National Laboratory. A necessary, but often overlooked, criterion of grid-convergence is ensured by using Adaptive Mesh Refinement (AMR) for both diesel and gasoline. Nine different realizations were performed and the effects of random seeds on spray behavior were investigated.

An ultrahigh injection pressure, common rail fuel injection system was designed, fabricated, and evaluated. The result was a system suitable for high-power density diesel engine applications. The main advantages of the concept are a very short injection duration capability, high injection pressure independent of engine speed, a simplified electronic control valve, and good packaging flexibility. Two prototype injectors were developed. Tests were performed on an injector flow bench and in a single cylinder research engine. The first prototype delivered 320 mm3 within 2.5 milliseconds with a 2600 bar peak injection pressure. A conventional minisac nozzle was used. The second prototype employed a specially designed pintle nozzle producing a near-zero cone angle liquid jet impinging on a 9-mm cylindrical target centered on the piston bowl crown (OSKA-S system). The second prototype had the capability to deliver 316mm3 in 0.97ms.

Diesel-fueled, heavy-duty engines are critical to global economies, but unfortunately they are currently coupled to the rising price and challenging emissions of Diesel fuel. Public awareness and increasingly stringent emissions standards have made Diesel OEMs consider possible alternatives to Diesel, including electrification, fuel cells, and spark ignition. While these technologies will likely find success in certain market segments, there are still many applications that will continue to require the performance and liquid-fueled simplicity of Diesel-style engines. Three-way catalysis represents a possible low-cost and highly-effective pathway to reducing Diesel emissions, but that aftertreatment system has typically been incompatible with Diesel operation due to the prohibitively high levels of soot formation at the required stoichiometric fuel-air ratios. This paper explores a possible method of integrating three-way catalysis with Diesel-style engine operation.

Combustion is governed by only two phenomena: chemical reactions and mixing (i.e., transport of energy, species, and momentum). A Reynolds Averaged Navier-Stokes (RANS) turbulence model is commonly employed to account for the enhanced mixing due to the presence of turbulence in fluid flow. A RANS turbulence model enhances mixing by introducing a turbulent viscosity. The addition of a turbulent viscosity not only enhances mixing but it also eliminates smaller scales in the CFD simulation. Even though the turbulent viscosity eliminates smaller scales, it is common for RANS engine combustion simulations to be under-resolved. The lack of sufficient mesh resolution to resolve the remaining scales in a RANS combustion simulation may result in a significant sub-grid term that needs to be modeled. In the context of combustion simulation, it is shown that frequently this sub-grid term is significantly more important than Turbulent Chemistry Interaction terms (TCI).