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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.

Using natural gas in an internal combustion engine (ICE) is emerging as a promising way to improve thermal efficiency and reduce exhaust emissions. In the development of such engine platforms, computational fluid dynamics (CFD) plays a fundamental role in the optimization of geometries and operating parameters. One of the most relevant issues in the simulation of direct injection (DI) gaseous processes is the accurate prediction of the gas jet evolution. The simulation of the injection process for a gaseous fuel does not require complex modeling, nevertheless properly describing high-pressure gas jets remains a challenging task. At the exit of the nozzle, the injected gas is under-expanded, the flow becomes supersonic and shocks occur due to compressibility effects. These phenomena lead to challenging computational requirements resulting from high grid resolution and low computational time-steps.

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.

CAE tools are increasingly important in the automotive design process. In part, CAE tools can be useful in reducing the number of physical prototypes required during a product development effort. CFD tools can assess and predict cylinder charge motion for proposed designs, thereby limiting the need for prototype work. Though detailed combustion simulation results could help guide product development, the time required for such simulations limits their usefulness in the context of a production program. However equally valuable information can be obtained from gas exchange analyses which require less computation time and are run only from Intake Valve opening (IVO) to spark timing. Chemical kinetics is not included in this type of analysis. Using this approach, large numbers of configurations can be evaluated in a short period of time. Every passing year automotive engineers are challenged to attain higher fuel economy targets.

A full understanding and characterization of the near-field of diesel sprays is daunting because the dense spray region inhibits most diagnostics. While x-ray diagnostics permit quantification of fuel mass along a line of sight, most laboratories necessarily use simple lighting to characterize the spray spreading angle, using it as an input for CFD modeling, for example. Questions arise as to what is meant by the “boundary” of the spray since liquid fuel concentration is not easily quantified in optical imaging. In this study we seek to establish a relationship between spray boundary obtained via optical diffused backlighting and the fuel concentration derived from tomographic reconstruction of x-ray radiography. Measurements are repeated in different facilities at the same specified operating conditions on the “Spray A” fuel injector of the Engine Combustion Network, which has a nozzle diameter of 90 μm.

The dense spray region in the near-field of diesel fuel injection remains an enigma. This region is difficult to interrogate with light in the visible range and difficult to model due to the rapid interaction between liquid and gas. In particular, modeling strategies that rely on Lagrangian particle tracking of droplets have struggled in this area. To better represent the strong interaction between phases, Eulerian modeling has proven particularly useful. Models built on the concept of surface area density are advantageous where primary and secondary atomization have not yet produced droplets, but rather form more complicated liquid structures. Surface area density, a more general concept than Lagrangian droplets, naturally represents liquid structures, no matter how complex. These surface area density models, however, have not been directly experimentally validated in the past due to the inability of optical methods to elucidate such a quantity.

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 study is a continuation of previous work assessing the robustness of a Cummins XPI common rail injection system operating with gasoline-like fuel. All the hardware from the original study was retained except for the high pressure pump head and check valves which were replaced due to cavitation damage. An additional 400 hour NATO cycle was run on the refurbished fuel system to achieve a total exposure time of 800 hours and detect any other significant failure modes. As in the initial investigation, fuel system parameters including pressures, temperatures and flow rates were logged on a test bench to monitor performance over time. Fuel and lubricant samples were taken every 50 hours to assess fuel consistency, metallic wear, and interaction between fuel and oil. High fidelity driving torque and flow measurements were made to compare overall system performance when operating with both diesel and light distillate fuel.

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.

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.

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.

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.