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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.

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.

This work involves modeling internal and near-nozzle flows of a gasoline direct injection (GDI) nozzle. The Engine Combustion Network (ECN) Spray G condition has been considered for these simulations using the nominal geometry of the Spray G injector. First, best practices for numerical simulation of the two-phase flow evolution inside and the near-nozzle regions of the Spray G injector are presented for the peak needle lift. The mass flow rate prediction for peak needle lift was in reasonable agreement with experimental data available in the ECN database. Liquid plume targeting angle and liquid penetration estimates showed promising agreement with experimental observations. The capability to assess the influence of different thermodynamic conditions on the two-phase flow nature was established by predicting non-flashing and flashing phenomena.

The Reynolds stress turbulence model (RSM) has been developed to go beyond the Boussinesq hypothesis and to improve turbulence modeling of flows with significant mean streamline curvature and secondary flow. In this paper the RSM in commercial CFD software CONVERGE is tested for its performance and robustness when applying to complex flows. Several validation cases including flow over flat plate, vortex combustor, diesel engine spray and combustion were selected to test the RSM. The swirling flow in vortex combustor, non-reacting but vaporizing ECN Spray A (free jet) and Sandia small bore diesel engine case are used to demonstrate the benefits of the RSM over the widely used RNG k-epsilon model without model tuning. The vortex combustor case shows the RSM can provide good prediction for strong swirling flow. ECN spray A case was used to demonstrate that the RSM can accurately predict the liquid and vapor penetration lengths of a free jet under diesel engine conditions.

This paper presents a novel methodology to investigate engine behaviour using an original numerical approach based on the direct temporal coupling between IFP-ENGINE, a 1D engine simulation tool used for the simulation of the gas exchange system, and IFP-C3D, a 3D CFD code used to simulate combustion and pollutant emissions. The coupling method is used to compute steady conditions of the whole engine dynamic system but could also be applied for transient operating conditions. To demonstrate the capabilities of the model a 4-cylinder turbocharged gasoline engine is modelled at two different operating points and the comparison with experimental measurements is shown.

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.

Among the existing concepts to help improve the efficiency of spark ignition engines on low load operating points, Controlled Auto-Ignition™ (CAI™) is an efficient way to lower both fuel consumption and pollutant emissions at part load without major modifications of the engine design. The CAI™ concept is founded on the auto-ignition of a highly diluted gasoline-based mixture in order to reach high indicated efficiency and low pollutant emissions through a low temperature combustion. The high dilution rates needed to successfully obtain CAI™ combustion imply the use of unconventional valve lift strategies. To correctly control this combustion mode, the rate of dilution has to be precisely known. From a numerical point of view, this induces the need for a CFD tool suited for air path computations, the most relevant one being a 1D simulation approach.

Modern diesel engines operate under injection pressures varying from 30 to 200 MPa and employ combinations of very early and conventional injection timings to achieve partially homogeneous mixtures. The variety of injection and cylinder pressures, as well as injector dynamics, result in different injection rates, depending on the conditions. These variations can be captured by 1-D injection models that take into account the dynamics of the injector, the cylinder and injection pressures, and the internal geometry of the nozzle. The information obtained by these models can be used to provide initial and boundary conditions for the spray modeling in a 3-D combustion code. In this paper, a methodology for coupling a 1-D injection model with a 3-D combustion code for direct-injected diesel engines is presented. A single-cylinder diesel engine has been used to demonstrate the capabilities of the model under varying injection conditions.

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.

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.

The present study extends the recently developed KIVA-GA computer code to incorporate a generalized piston bowl geometry parameterization and multi-mode optimization. The new code was used to optimize the combustion chamber geometry of a small-bore automotive Diesel engine. The Genetic Algorithm (GA) merit function, which was calculated with a modified version of the KIVA-3V engine simulation code, included NOx, unburned HC, soot, and fuel consumption. A novel parameterization was included in KIVA-GA that allows for a variable number of parameters to define the bowl shape. The in-house G-Smooth grid generation package was used to create the KIVA grids with a specified compression ratio and mesh resolution. The improved KIVA-GA methodology was used to optimize engine emissions and performance simultaneously for two operating conditions.

Recent measurements by Siebers et al. have shown that the flame of a high pressure Diesel spray stabilizes under quiescent conditions at a location downstream of the fuel injector. The effects of various ambient and injection parameters on the flame “lift-off” length have been investigated under typical Diesel conditions in a constant-volume combustion vessel. In the present study, the experiments of Siebers et al. have been modeled using a modified version of the KIVA-3V engine simulation code. Fuel injection and spray breakup are modeled using the KH-RT model that accounts for liquid surface instabilities due to the Kelvin-Helmholtz and Rayleigh-Taylor mechanisms. Combustion is simulated using Convergent Thinking's recently developed detailed transient chemistry solver (SAGE) that allows for any number of chemical species and reactions to be modeled.

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 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).

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.

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.

Interest in operational cost reduction is driving engine manufacturers to consider low-cost fuel substitution in heavy-duty diesel engines. These dual-fuel (DF) engines could be operated either in diesel-only mode or operated with premixed natural gas (NG) ignited by a pilot flame of compression-ignited direct-injected diesel fuel. Under certain conditions, dual-fuel operation can result in increased cycle-to-cycle variability (CCV) during combustion. CFD can greatly help in understanding and identifying critical parameters influencing CCV. Innovative modelling techniques and large computing resources are needed to investigate the factors affecting CCV in dual-fuel engines. This paper discusses the use of the High Performance Computing resource Titan, at Oak Ridge National Laboratory, to investigate CCV of a dual-fuel engine.

The numerical simulation of internal aerodynamic of automotive combustion chamber is characterised by complex displacements of moving elements (piston, intake/exhaust valves…) and by a strong variation of volume that cause some problems with classical numerical based mesh methods. With those methods (FEM, FVM) which use geometric polyhedral elements (hexaedron, tetrahedron, prismes…), it is necessary to change periodically the mesh to adapt the grid to the new geometry. This step of remeshing is very fastidious and costly in term of engineer time and may reduce the precision of calculation by numerical dissipation during the interpolation process of the variables from one mesh to another. Recently, the researcher community has renewed his interest for the development of a generation of numerical to circumvent the drawbacks of the classical methods.

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 standard capability of engine experimental studies is that ensemble averaged quantities like in-cylinder pressure from multiple cycles and emissions are reported and the cycle to cycle variation (CCV) of indicated mean effective pressure (IMEP) is captured from many consecutive combustion cycles for each test condition. However, obtaining 3D spatial distribution of all the relevant quantities such as fuel-air mixing, temperature, turbulence levels and emissions from such experiments is a challenging task. Computational Fluid Dynamics (CFD) simulations of engine flow and combustion can be used effectively to visualize such 3D spatial distributions. A dual fuel engine is considered in the current study, with manifold injected natural gas (NG) and direct injected diesel pilot for ignition.