Efficient and Effective CFD Design Flow for Internal   Combustion Engines          March 14, 2010        REACTION DESIGN  ...
Traditional IC engine combustion simulations involve CFD models that use a simplified chemistryrepresentation for fuel com...
spent adjusting or adding complexity to the mesh, to find the optimal combination of spray-modelparameters and grid. Probl...
Figure 1: CFD design flow  The ideal CFD design flow      •   Go directly from CAD drawings into running CFD cases      • ...
combustion, or alternative fuels are present. The overall success of a predictive CFD design flow dependsnot only on the a...
Figure 3: Dramatically reducing chemistry calculation time in CFD allow the use of more accurate          chemistry for go...
account for 90% of the total simulation time even when employing severely reduced mechanisms, there issubstantial opportun...
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Efficient and Effective CFD Design Flow for Internal Combustion Engines

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Traditional IC engine combustion simulations involve CFD models that use a simplified chemistry
representation for fuel combustion. The chemistry in the models range from just a few molecular species
to ~50 species for Diesel fuel, for example. Alternative approaches use table-lookup strategies and progress variables to avoid the cost of direct computation of the chemistry-flow interactions. For conventional Diesel and Gasoline engines, these approaches have historically been good enough, because
the fluid-mixing effects dominated the kinetics effects in predicting engine performance. This whitepaper discusses a more efficient and effective CFD design flow for IC engines.

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Efficient and Effective CFD Design Flow for Internal Combustion Engines

  1. 1. Efficient and Effective CFD Design Flow for Internal Combustion Engines March 14, 2010 REACTION DESIGN www.reactiondesign.com +1 858-550-1920
  2. 2. Traditional IC engine combustion simulations involve CFD models that use a simplified chemistryrepresentation for fuel combustion. The chemistry in the models range from just a few molecular speciesto ~50 species for Diesel fuel, for example. Alternative approaches use table-lookup strategies andprogress variables to avoid the cost of direct computation of the chemistry-flow interactions. Forconventional Diesel and Gasoline engines, these approaches have historically been good enough, becausethe fluid-mixing effects dominated the kinetics effects in predicting engine performance.New engine designs present new simulation challengesNew, high-efficiency, low-emissions designs present technical challenges that are dominated by kinetics(e.g., dual-fuel engines, staged spray injections for improved efficiency, Premixed Charge CompressionIgnition (PCCI) combustion, low temperature conditions, etc.). What proved to be good enough for thedesign of yesterdays engines is insufficient for todays new engine designs. A consistent complaint by theindustry is that they cannot rely on combustion CFD to predict values or even accurate trends in criticalcombustion behaviors such as ignition, flame propagation and emissions. This problem is exacerbated bythe fact that the fuels landscape continues to evolve and become more complex. Where yesterday’sengines were designed for a single fuel type, such as diesel or gasoline, todays engine specificationsdemand fuel flexibility while achieving ultralow emissions.The Model Fuels Consortium is an industry-led program, currently in its sixth year, which has developedboth the detailed chemical mechanisms and the tools required to simulate real fuel behavior. While theMFC has been exceedingly successful in developing fuel mechanisms that accurately simulate real fuelchemistry, it has proved the impracticality of reducing these mechanisms they can be incorporated intocontemporary CFD simulations without a substantial loss in accuracy. MFC researchers have recognizedthat the focus should shift from trying to get reliable results with mechanisms so severely reduced thatthey cannot capture real fuel behavior, to enhancing the ability of simulation tools to use mechanismswith the necessary level of detail.One of the Department of Energy’s premier scientific laboratories studying engine efficiency recentlyacknowledged the critical link between the need to reduce greenhouse gas emissions and advancedsimulation in a white paper entitled: “Predictive Simulation of Combustion Engine Performance in anEvolving Fuel Environment.”i The paper points out that engine manufacturers must move to “changefrom a test-first culture to an Analysis-Led Design Process” and that “a predictive simulation toolkitwould accelerate the market transformation to high-efficiency, clean power sources for transportation.”Kinetics is recognized as a critical area for advancement supporting the design of clean, fuel-flexibleengines that reduce greenhouse gas emissions.Another key area of concern in engine simulation has been spray modeling. The choice of the spraymodel can have a significant impact on both time-to-solution and the accuracy of results. Most of thespray models used today are highly mesh dependent, which requires that valuable innovation time beReaction Design 1
  3. 3. spent adjusting or adding complexity to the mesh, to find the optimal combination of spray-modelparameters and grid. Problematically, this approach requires that the behavior of the spray in thecylinder is known in order to tune the model to predict it. Even when a spray model can be calibrated toa particular grid, it is unclear how effective the model will be on a different engine design, which mayrequire the whole process to be repeated. Understanding how to do this calibration requires specificexpertise and makes it difficult for widespread utilization of predictive CFD across the organization.The lack of reliability in combustion simulations is likely caused by a lack of detail in the way the fuel-spray and combustion kinetics are represented. Because the industry has been limited in the amount ofchemistry detail it could practically incorporate into a simulation, work has focused on turbulence-mixing phenomena, use of approximate combustion models, and meshing. But, because of theincreasing challenges in today’s engine design environment, attention is once again turning to improvedmodeling of the spray and kinetic phenomena.How engine designers address the challenges todayThe dominant way of dealing with time-to-solution issues over the last five years was simply to buy moreCPUs and use brute force to get a solution in a reasonable amount of time. Unfortunately, the inherentlimitations of conventional CFD approaches prevent the use of larger, more accurate mechanisms due tosolution complexity and numerical stability issues. Another common approach was to employ severelyreduced chemical mechanisms in CFD simulations, hoping that important combustion behavior might bepredicted even though most of the details had been removed. This approach worked for conventionalengine design by relying on vast amounts of empirical performance data, but these data do not exist fortoday’s novel engine designs.Some in the industry claim that predictive results are not achievable without engine calibration. Thismeans that in the end, the price of an inaccurate model is using extensive data to “tune” the simulationmodel. The tuned CFD approach, however, often fails to translate to good results under different engineoperating conditions. This prevents in-cylinder combustion CFD from being a truly predictive designtool. The impact of the lack of reliable results from existing CFD approaches is that production designengineers cannot use them efficiently and this work must be done by expert R&D personnel oroutsourced to groups with specific expertise. Sometimes, combustion simulation is avoided completelyand non-reacting simulations are used to identify parameters such as local fuel/air ratio or spraydistribution and used to infer the effect on combustion performance.Reaction Design 2
  4. 4. Figure 1: CFD design flow The ideal CFD design flow • Go directly from CAD drawings into running CFD cases • Easy, graphical setup of the CFD case • Incorporate experimental results as inputs to the CFD case • Create parameter studies to conduct Design of Experiments on operating conditions • Accurate fuel chemistry models to predict real fuel behavior and emissions formation • Incorporate spray models that are truly predictive and independent of mesh size • Spark ignition models must accurately and efficiently track the ignition, flame propagation and onset of knock for today’s fuel and engine designs • Powerful and smart chemistry solvers to tackle the daunting challenge of using accurate chemistry • Seamlessly create, view and analyze the CFD results that an engine designer cares about without the use of postprocessor at additional expense. Treating each of these areas as point solutions builds inefficiencies into the CFD design flow that can have dramatic impacts on its effectiveness. Improvements in one facet of the flow can slow down other facets or affect accuracy. Weak or disjointed links in the flow can cause unnecessary delays or a loss of information that also hinder CFD’s value as an effective design tool. Meshing can be handled automatically or adaptively, but it can also generate a substantially larger number of cells or introduce numerical errors that negatively impact run time and accuracy. Command-line software interfaces require engineers to master a series of arcane user inputs and serve to inhibit wide use by developers. Using progress variables and lookup tables as ways to manage computational complexity can also impair the ability of CFD to be used as a predictive tool on cases where either high-EGR, low-temperature Reaction Design 3
  5. 5. combustion, or alternative fuels are present. The overall success of a predictive CFD design flow dependsnot only on the accuracy of the simulation results, but also on the timeliness and ease of generating thoseresults.A new approach: achieving accuracy by modeling real fuel chemistryFor advanced-concept engines, chemical kinetics takes a front-seat role in controlling ignition behavior, aswell as emission and knock performance. Managing uncertainties in fuels and fuel composition requiresuse of a high-fidelity fuel model in design calculations. Traditional CFD models are stymied by theserequirements, forcing designers to rely on expensive empirical methods for exploring and verifying newideas.Powerful chemistry solutionsThe barrier to good fuel representation in CFD simulations is not the lack of information about thedetailed chemical kinetics of fuel combustion. In fact, there has been huge growth in the understandingof the combustion behavior of liquid transportation fuels over the last decade through work validated bythe Model Fuels Consortium. A surrogate-fuel approach was used in fuel-combustion studies, where asmall set of fuel-component molecules were selected to represent real fuels. In conjunction with this, theMFC developed very detailed, molecular-based kinetics representations of the important surrogate fuelcomponents for conventional and alternative automotive fuels. Consortium researchers showed thatsurrogate-fuel models that employ fundamental chemical kinetics information can capture details of fuelignition, flame propagation, pollutant emissions, particulate formation and engine knocking, as well asthe effects of fuel variability and multi-fuel strategies.Results demonstrate both quantitative and qualitative prediction capability for combustion behavior, asseen in Figure 2, where a reduced mechanism with ~100 species are compared to a more accuratemechanism with 428 species. Experimental data are represented by the solid triangles. The largermechanism is shown to have sufficient accuracy required to provide excellent prediction of emissionsvalues and trends.Figure 2: Dramatic improvement in the accuracy of CFD emissions results when using an accuratemechanism with 428 species (solid line) compared to a reduced mechanism with ~100 species (dashed line).Reaction Design 4
  6. 6. Figure 3: Dramatically reducing chemistry calculation time in CFD allow the use of more accurate chemistry for good results without expert calibration.Critical time time-to-solution advancement: Automatic Mesh GenerationCreating meshes for internal combustion engines is difficult. The typical engine CFD design projectbegins with a lengthy process to construct an adequate representation of the cylinder and port geometryusing a mesh of computational cells. The construction must account for the fact that the mesh musttransform and shift dynamically with the motion of pistons and valves during the engine cycle. Thisprocess can take weeks for a single-cylinder configuration, making a design- of-experiments thatconsiders geometry changes particularly challenging. Mesh generation has become the realm of a limitednumber of experts who know all the tricks that are required to get an accurate and robust mesh.Automatic mesh generation eliminates a key bottleneck from the design flow by importing CADdrawings directly into the CFD environment. The key to success of this automation strategy is to ensurethat the implementation neither slows down other phases of the design flow nor introduces errors. Froman accuracy point of view, the ideal mesh created is one that is Cartesian, with perfectly orthogonal faces,and one in which the boundary conditions are enforced exactly on the physical surfaces of the realgeometry. Automatic-mesh-generation methods that use a pure Cartesian based system avoid theproblems of highly skewed cells that can be introduced with other approaches.Can you get accuracy in combustion CFD with reasonable solution times?This is certainly the key question and time-to-solution has been a key barrier to incorporating sufficientchemistry accuracy into CFD calculations. As most commercial CFD improvements directed towardbetter accuracy have focused on enhancing meshing and turbulence modeling, there has been little effortdirected toward improving the fundamental chemistry calculations, to reflect the key engine behaviorsthat are now beginning to dominate the design space. Given that chemistry calculation times in CFD canReaction Design 5
  7. 7. account for 90% of the total simulation time even when employing severely reduced mechanisms, there issubstantial opportunity for decreasing time-to-solution by accelerating these calculations.Reaction Design’s CFD package, called FORTÉ, employs a novel solver approach that takes advantage ofthe chemical similarity of groups of cells and implements a parallel processing algorithm to dramaticallyreduce the chemistry calculation time. This technique can reduce simulation run times by almost twoorders of magnitude, as demonstrated in Figure 3. Chemistry models that previously were thought of asonly practical for 0-D simulations are now practical for full 3-D engine simulations complete with movingpistons and valves. With innovative approaches to relieving the bottleneck in chemistry calculations,predictive engine simulation is now a reality.Referencei“Predicting Simulation of Combustion Engine Performance in an Evolving Fuel Environment,” US DOE SandiaWhite Paper, submitted by Robert W. Carling, February 25, 2010.Reaction Design 6

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