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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 state-of-the-art spray modeling methodology, recently applied to RANS simulations, is presented for LES calculations. Key features of the methodology, such as Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, are described. The ability of this approach to use cell sizes much smaller than the nozzle diameter is demonstrated. Grid convergence of key parameters is verified for non-evaporating and evaporating spray cases using cell sizes down to 1/32 mm. It is shown that for global quantities such as spray penetration, comparing a single LES simulation to experimental data is reasonable, however for local quantities the average of many simulated injections is necessary. Grid settings are recommended that optimize the accuracy/runtime tradeoff for LES-based spray simulations.

Ammonia is a promising carbon-free alternative fuel for use in combustion systems. The main associated challenges are its relatively low reactivity and high NOx emissions compared to conventional fuels. Therefore, the combustion behaviour of ammonia and ammonia blends still needs to be better understood over a wide range of conditions. To this end, a comprehensive chemical kinetic mechanism C3MechV3.4, which is an update of C3MechV3.3, has been developed for improved predictions of the combustion of ammonia and ammonia blends. C3MechV3.4 has been validated using a wide range of experimental results for pure ammonia and ammonia/hydrogen, ammonia/methanol and ammonia/n-heptane blends. These validations target different data sets including ignition delay times, species profiles measured as a function of time, and/or temperature and laminar flame speeds over a wide range of conditions.

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 Computational Chemistry Consortium (C3) is dedicated to leading the advancement of combustion and emissions modeling. The C3 cluster combines the expertise of different groups involved in combustion research aiming to refine existing chemistry models and to develop more efficient tools for the generation of surrogate and multi-fuel mechanisms, and suitable mechanisms for CFD applications. In addition to the development of more accurate kinetic models for different components of interest in real fuel surrogates and for pollutants formation (NOx, PAH, soot), the core activity of C3 is to develop a tool capable of merging high-fidelity kinetics from different partners, resulting in a high-fidelity model for a specific application. A core mechanism forms the basis of a gasoline surrogate model containing larger components including n-heptane, iso-octane, n-dodecane, toluene and other larger hydrocarbons.

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.

Fuel injection characteristics, in particular the atomization and penetration of the fuel droplets in the region close to the nozzle orifice, are known to affect emission and particulate formation in Diesel engines. It is also well established that the primary fuel atomization process is induced by aerodynamics in the near nozzle region as well as cavitation and turbulence from the injector nozzle. Typical breakup models in the literature however, do not consider the effects of cavitation and turbulence from nozzle injector. In this paper, a comprehensive primary breakup model incorporating the inner nozzle flow effects such as cavitation and turbulence along with aerodynamically induced breakup is developed and incorporated in the CONVERGE CFD code. This new primary breakup model is tested in a constant volume spray chamber against various spray data available in the literature.

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.

This paper implements a coupled approach to integrate the internal nozzle flow and the ensuing fuel spray using a Volume-of-Fluid (VOF) method in the CONVERGE CFD software. A VOF method was used to model the internal nozzle two-phase flow with a cavitation description closed by the homogeneous relaxation model of Bilicki and Kestin [1]. An Eulerian single velocity field approach by Vallet et al. [2] was implemented for near-nozzle spray modeling. This Eulerian approach considers the liquid and gas phases as a complex mixture with a highly variable density to describe near nozzle dense sprays. The mean density is obtained from the Favreaveraged liquid mass fraction. The liquid mass fraction is transported with a model for the turbulent liquid diffusion flux into the gas.

This paper delves into the intricate realm of Formula 1 race car aerodynamics, focusing on the pivotal role played by floor flow structures in contemporary racing. The aerodynamic design of the floor of a Formula 1 car is a fundamental component that connects the flow structures from the front wing to the rear end of the car through the diffuser, thus significantly influencing the generation of lift and drag. In this work, CFD was used to predict the structure of the vortices and flow pattern underneath a Formula 1 car using a CAD model that mimicked the modern Red Bull Racing Team’s car in recent years. Through comprehensive analysis and simulation, a detailed understanding of the complex flow patterns and aerodynamic phenomena occurring beneath the floor of the car and its vicinity is presented.

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.

Reduced-order models typically assume that the flow through the injector orifice is quasi-steady. The current study investigates to what extent this assumption is true and what factors may induce large-scale variations. Experimental data were collected from a single-hole metal injector with a smoothly converging hole and from a transparent facsimile. Gas, likely indicating cavitation, was observed in the nozzles. Surface roughness was a potential cause for the cavitation. Computations were employed using two engineering-level Computational Fluid Dynamics (CFD) codes that considered the possibility of cavitation. Neither computational model included these small surface features, and so did not predict internal cavitation. At steady state, it was found that initial conditions were of little consequence, even if they included bubbles within the sac. They however did modify the initial rate of injection by a few microseconds.

Lagrangian particle tracking has proven very useful for IC engine spray simulations. However, traditional techniques have been very susceptible to grid dependency. As a consequence, predicted engine performance can depend on the computational mesh. The two main causes of this problem are the collision algorithm and the inter-phase coupling. Using the No Time Counter droplet collision algorithm with an embedded collision mesh practically eliminates grid dependency as a consequence of the collision algorithm. The remaining grid dependency is due to numerical error of the gas phase near the injector and problems with coupling the gas phase and liquid phase. Calculations were made using a novel interpolation scheme that takes advantage of the polar symmetry in the spray. The scheme transforms the velocities into their polar components before doing interpolation. The results show a dramatic decrease in grid dependency.