Search Results

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.

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.

Fuels in the gasoline auto-ignition range (Research Octane Number (RON) > 60) have been demonstrated to be effective alternatives to diesel fuel in compression ignition engines. Such fuels allow more time for mixing with oxygen before combustion starts, owing to longer ignition delay. Moreover, by controlling fuel injection timing, it can be ensured that the in-cylinder mixture is “premixed enough” before combustion occurs to prevent soot formation while remaining “sufficiently inhomogeneous” in order to avoid excessive heat release rates. Gasoline compression ignition (GCI) has the potential to offer diesel-like efficiency at a lower cost and can be achieved with fuels such as low-octane straight run gasoline which require significantly less processing in the refinery compared to today’s fuels.

Diesel engine pollutant emissions legislation is becoming more and more stringent. New driving cycles, including increasingly severe transient engine operating conditions and low ambient-temperature conditions, extend considerably the engine operating domain to be optimized to attain the expected engine performance. Technological innovations, such as high pressure injection systems, Exhaust Gas Recirculation (EGR) loops and intake pressure boosting systems allow significant improvement of engine performance. Nevertheless, because of the high number of calibration parameters, combustion optimization becomes expensive in terms of resources. System simulation is a promising tool to perform virtual experiments and consequently to reduce costs, however models must account for relevant in-cylinder physics to be sensitive to the impact of technology on combustion and pollutant formation.

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.

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 accurate modeling of fuel spray behavior under diesel engine conditions requires well-characterized boundary conditions. Among those conditions, the spray cone angle is important due to its impact on the spray mixing process, flame lift-off locations and subsequent soot formation. The spray cone angle is a highly dynamic variable, but existing correlations have been developed mainly for diesel fuels at quasi-steady state and relatively low injection pressures. The objective of this study was to develop spray cone angle correlations for both diesel and a light-end gasoline fuel over a wide range of diesel-engine operating conditions that are capable of capturing both the transient and quasi-steady state processes. Two important macroscopic characteristics of solid cone sprays, the spray cone angle and spray penetration, were measured using a single-hole heavy-duty injector using two fuels at diesel engine conditions in an optical constant volume vessel.

Detailed chemical kinetics, although preferred due to increased accuracy, can significantly slow down CFD combustion simulations. Chemistry solutions are typically the most computationally costly step in engine simulations. The calculation time can be significantly accelerated using a multi-zone combustion model. The multi-zone model is integrated into the CONVERGE CFD code. At each time-step, the CFD cells are grouped into zones based on the cell temperature and equivalence ratio. The chemistry solver is invoked only on each zone. The zonal temperature and mass fractions are remapped onto the CFD cells, such that the temperature and composition non-uniformities are preserved. Two remapping techniques published in the literature are compared for their relative performance. The accuracy and speed-up of the multi-zone model is improved by using variable bin sizes at different temperature and equivalence ratios.

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.

EGR systems are widely applied in modern turbocharged diesel engines to reduce engine-out emissions and will, or are being used to mitigate engine knock in SI engines for improved SI engine efficiency and power. In this paper, different EGR systems are detailed and evaluated theoretically based on the thermodynamics of a turbocharged system featuring an EGR sub-system. Turbine expansion ratio is utilized as a metric to estimate engine efficiency, i.e., pumping losses during the gas exchange process. Approaches such as compressor and turbine bypassing are evaluated as well. Based on above analysis, a new approach is put forward to expand the turbocharger work zone, particularly in the high efficiency regions by correctly utilizing EGR systems at all engine speed range: low-pressure loop EGR system at lower engine speed range and high-pressure loop EGR system at high engine speed range.

Urea water solution-based Selective Catalytic Reduction (SCR) of NOx emissions from vehicular diesel engines is now widely used world-wide to meet strict health and environmental protection regulations. While urea-based SCR is proven effective, urea-derived deposits often form near injectors, on mixers and pipes, and on the SCR catalyst face. Further understanding of these deposit-formation processes is needed to design aftertreatment system hardware and control systems capable of avoiding severe urea-derived deposits. Computational Fluid Dynamics (CFD) is widely used in SCR aftertreatment design. Film formation, movement, solid wall cooling and deposit initiation/growth time-scales are in the range of minutes to hours, but traditional CFD simulations take too long to reach these time-scales. Here, we propose and demonstrate the frozen flow approach for pulsed sprays and conjugate heat transfer to reduce computation time while maintaining accuracy of key physics.

In order to assist in fast design cycle of Diesel engines selective catalytic reduction (SCR) exhaust systems, significant endeavor is currently being made to improve numerical simulation accuracy of urea thermo-hydrolysis. In this article, the achievements of a recently developed urea semi-detailed decomposition chemical scheme are assessed using three available databases from the literature. First, evaporation and thermo-hydrolysis of urea-water solution (UWS) single-droplets hanged on a thin thermocouple ring (127 μm) as well as on a thick quartz (275 μm), have been simulated at ambient temperature conditions ranging from 473K to 773K. It has been shown that the numerical results, in terms of evaporation rate and urea gasification, as well as droplet temperature history are very close to the experiments if the heat flux coming from the droplet support is properly accounted for.

Recent research has shown that gasoline compression ignition (GCI) improves the soot-NOx tradeoff of traditional diesel engines due to the beneficial properties of light distillate fuels. However, system level optimization of a new engine concept is ultimately needed to maximize fuel economy and emissions improvements. Along with air and aftertreatment systems, the fuel system also requires further development to enable GCI. One important design tool for fuel system hardware is 1-D hydraulic modeling. Although accurate tabulations of diesel or equivalent calibration fluid properties are available in 1-D modelling software packages, the same situation does not exist for gasoline-like fuels, especially at conditions encountered in the high-pressure injection equipment needed to support GCI. This study presents a methodology for generating accurate liquid property databases of complex, multi-component light distillate fuels that can be used in high-pressure 1-D hydraulic models.

Urea-water solution (UWS) injection combined with Selective Catalytic Reduction (SCR) has developed as an effective method of meeting EPA and EURO NOx emissions regulations for diesel engines. Urea/SCR systems encompass a wide range of engine sizes, from light duty vehicles to large ship or power generation engines. One key challenge faced by modern urea/SCR systems is the formation of solid deposits of urea decomposition by-products that are difficult to remove. These deposits are proven to be detrimental to urea/SCR systems by decreasing ammonia uniformity, clogging injector nozzles and increasing pressure drop of the whole system. Urea deposits only form in a narrow range of wall temperatures and take many minutes to hours to form. The decomposition of urea into deposits begins with the formation of biuret and then progresses into the crystalline species cyanuric acid (CYA), ammelide, and ammeline.

Fluid-Structure Interaction (FSI) simulation approach can be used to simulate a turbocharger. However, this predictive 3D simulation encounters the challenge of a long computational time. The impeller speed can be above 100,000 rpm, and generally a CFD solver limits the maximum movement of the impeller surface per time step. The maximum movement must be a fraction (~0.3) of the cell length, thus the time step will be very small. A Multiple Reference Frame (MRF) approach can reduce computational time by eliminating the need to regenerate the mesh at each time-step to accommodate the moving geometry. A static local reference zone encompassing the impeller is created and the impact of the impeller movement is modeled via a momentum source. However, the MRF approach is not a predictive simulation because the impeller speed must be given by the User. A new simulation approach was introduced that coupled the FSI and MRF approach.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NOx within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions.