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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.

Shock waves have been recently observed in high-pressure diesel sprays. In this paper, three-dimensional numerical simulations of supersonic diesel spray injection have been performed to investigate the underlying dynamics of the induced shock waves and their interactions with the spray. A Volume-of-Fluid based method in the CFD software (CONVERGE) is used to model this multiphase phenomena. An adaptive Mesh Refinement (AMR) scheme is employed to capture the front of the spray and the shock waves with high fidelity. Simulation results are compared to the available experimental observations to validate the numerical procedure. Parametric studies with different injection and ambient conditions are conducted to examine the effect of these factors on the generation of shock waves and their dynamics.

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).

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.

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.

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.

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.

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.

In-cylinder fluid velocity is measured in an optically accessible, fired HSDI engine at idle. The velocity field is also calculated, including the full induction stroke, using multi-dimensional fluid dynamics and combustion simulation models. A detailed comparison between the measured and calculated velocities is performed to validate the computed results and to gain a physical understanding of the flow evolution. Motored measurements are also presented, to clarify the effects of the fuel injection process and combustion on the velocity field evolution. The calculated mean in-cylinder angular momentum (swirl ratio) and mean flow structures prior to injection agree well with the measurements. Modification of the mean flow by fuel injection and combustion is also well captured.

Experimental data is used in conjunction with multi-dimensional modeling in a modified version of the KIVA-3V code to characterize the emissions behavior of a high-speed, direct-injection diesel engine. Injection pressure and EGR are varied across a range of typical small-bore diesel operating conditions and the resulting soot-NOx tradeoff is analyzed. Good agreement is obtained between experimental and modeling trends; the HSDI engine shows increasing soot and decreasing NOx with higher EGR and lower injection pressure. The model also indicates that most of the NOx is formed in the region where the bulk of the initial heat release first takes place, both for zero and high EGR cases. The mechanism of NOx reduction with high EGR is shown to be primarily through a decrease in thermal NOx formation rate.