Efficient and Effective CFD

Design Flow for Internal

Combustion Engines

April 23, 2012

REACTION DESIGN

www.reactiondesign.com

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Traditional IC engine combustion simulations involve CFD models that use simplified representations of
fuel sprays and combustion chemistry. Spray models are typically quite sensitive to the mesh resolution
and parameters need constant calibration. The chemistry in the models range from just a few molecular
species to ~50 species for Diesel fuel, for example. Alternative approaches to direct incorporation of
chemistry 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 may
have historically been good enough, because the fluid-mixing effects dominated the kinetics effects in
predicting engine performance.

New engine designs present new simulation challenges

New, 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 Compression
Ignition (PCCI) combustion, low temperature conditions, etc.). What proved to be good enough for the
design of yesterday's engines is insufficient for today's new engine designs. A consistent complaint by the
industry is that they cannot rely on combustion CFD to predict values or even accurate trends in critical
combustion behaviors such as ignition, flame propagation and emissions. This problem is exacerbated by
the fact that the fuels landscape continues to evolve and become more complex. Where yesterday’s
engines were designed for a single fuel type, such as diesel or gasoline, today's engine specifications
demand fuel flexibility while achieving ultralow emissions.

The Model Fuels Consortium is an industry-led program, currently in its sixth year, which has developed
both the detailed chemical mechanisms and the tools required to simulate real fuel behavior. While the
MFC has been exceedingly successful in developing fuel mechanisms that accurately simulate real fuel
chemistry, it has proved the impracticality of reducing these mechanisms so they can be incorporated into
contemporary CFD simulations without a substantial loss in accuracy. MFC researchers have recognized
that the focus should shift from trying to get reliable results with mechanisms so severely reduced that
they cannot capture real fuel behavior, to enhancing the ability of simulation tools to use mechanisms
with the necessary level of detail.

One of the Department of Energy’s premier scientific laboratories studying engine efficiency recently
acknowledged the critical link between the need to reduce greenhouse gas emissions and advanced
simulation in a white paper entitled: “Predictive Simulation of Combustion Engine Performance in an
Evolving Fuel Environment.”

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The paper points out that engine manufacturers must move to “change

from a test-first culture to an Analysis-Led Design Process” and that “a predictive simulation toolkit
would 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-flexible
engines that reduce greenhouse gas emissions.

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Another key area of concern in engine simulation has been spray modeling. The choice of the spray
model can have a significant impact on both time-to-solution and the accuracy of results. Most of the
spray models used today are highly mesh-dependent, which requires that valuable innovation time be
spent adjusting or adding complexity to the mesh, to find the optimal combination of spray-model
parameters and grid. Problematically, this approach requires that the behavior of the spray in the
cylinder is known in order to tune the model to predict it. Even when a spray model can be calibrated to
a particular grid, it is unclear how effective the model will be on a different engine design, which may
require the whole process to be repeated. Understanding how to do this calibration requires specific
expertise, which is a barrier to 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 of
chemistry 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 the
increasing challenges in today’s engine-design environment, attention is once again turning to improved
modeling of the spray and kinetic phenomena.

How engine designers address the challenges today

The dominant way of dealing with time-to-solution issues now is to buy more CPUs in order to get a
solution in a reasonable amount of time. Unfortunately, even with this approach the inherent limitations
of conventional CFD solution algorithms prevent the use of larger, more accurate mechanisms due to
numerical stability issues. Another common approach has been to employ severely reduced chemical
mechanisms in CFD simulations, hoping that important combustion behavior might be predicted even
though most of the details have been removed. This approach worked for conventional engine design by
relying on vast amounts of empirical performance data, but these data do not exist for today’s novel
engine designs.

Some in the industry claim that accurate results are not achievable without constant re-calibration against
engine data. This means that in the end, the price of an inaccurate model is using extensive data to
“tune” the simulation. The tuned CFD approach, however, usually fails to translate to good results under
different engine operating conditions. This prevents in-cylinder combustion CFD from being a truly
predictive design tool. The impact of the lack of reliable results from existing CFD approaches is that
production design engineers cannot use them efficiently and this work must be done by expert R&D
personnel or outsourced to groups with specific expertise. Sometimes, combustion simulation is avoided
completely and non-reacting simulations are used to identify parameters such as local fuel/air ratio or
spray distribution and used to infer the effect on combustion performance.

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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 care must be taken that such meshes do not force the use of excessively
large numbers of cells, tiny 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

Figure 1: CFD design flow

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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 combustion, or alternative fuels are present. The overall
success of a predictive CFD design flow depends not only on the accuracy of the simulation results, but
also on the timeliness and ease of generating those results.

A new approach: Achieving accuracy by modeling real fuel chemistry

For advanced-concept engines, chemical kinetics takes a front-seat role in controlling ignition behavior, as
well as emission and knock performance. Managing uncertainties in fuels and fuel composition requires
use of a high-fidelity fuel model in design calculations. Traditional CFD models are stymied by these
requirements, forcing designers to rely on expensive empirical methods for exploring and verifying new
ideas.

Powerful chemistry solutions

The barrier to good fuel representation in CFD simulations is not the lack of information about the
detailed chemical kinetics of fuel combustion. In fact, there has been huge growth in the understanding
of the combustion behavior of liquid transportation fuels over the last decade through work validated by
the Model Fuels Consortium. A surrogate-fuel approach was used in fuel-combustion studies, where a
small set of fuel-component molecules were selected to represent real fuels. In conjunction with this, the
MFC developed very detailed, molecular-based kinetics representations of the important surrogate fuel
components for conventional and alternative automotive fuels. Consortium researchers showed that
surrogate-fuel models that employ fundamental chemical kinetics information can capture details of fuel
ignition, flame propagation, pollutant emissions, particulate formation and engine knocking, as well as
the effects of fuel variability and multi-fuel strategies.

Results demonstrate both quantitative and qualitative prediction capability for combustion behavior, as
seen in Figure 2, where a reduced mechanism with ~100 species is compared to a more accurate
mechanism with 428 species. Experimental data are represented by the solid triangles. The larger
mechanism is shown to have sufficient accuracy to provide excellent prediction of emissions values and
trends.

Figure 2: Dramatic improvement in the accuracy of CFD emissions results when using an accurate
mechanism with 428 species (solid line) compared to a reduced mechanism with ~100 species (dashed line).

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Critical time time-to-solution advancement: Automatic Mesh Generation

Creating meshes for internal combustion engines is difficult. The typical engine CFD design project
begins with a lengthy process to construct an adequate representation of the cylinder and port geometry
using a mesh of computational cells. The construction must account for the fact that the mesh must
transform and shift dynamically with the motion of pistons and valves during the engine cycle. This
process can take weeks for a single-cylinder configuration, making a design-of-experiments that
considers geometry changes particularly challenging. Mesh generation has become the realm of a limited
number 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 CAD
drawings directly into the CFD environment. The key to success of this automation strategy is to ensure
that the implementation neither slows down other phases of the design flow nor introduces errors. From
an 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 real
geometry. Automatic-mesh-generation methods that use a pure Cartesian-based system avoid the
problems 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 sufficient
chemistry accuracy into CFD calculations. As most commercial CFD improvements directed toward
better accuracy have focused on enhancing meshing and turbulence modeling, there has been little effort
directed toward improving the fundamental chemistry calculations, to reflect the key engine behaviors
that are now beginning to dominate the design space. Given that chemistry calculation times in CFD can
account for 90% of the total simulation time even when employing severely reduced mechanisms, there is
substantial 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 of
the chemical similarity of groups of cells and implements a parallel processing algorithm to dramatically
reduce the chemistry calculation time. This technique can reduce simulation run times by almost two
orders of magnitude, as demonstrated in Error! Reference source not found.. Chemistry models that
previously were thought of as only practical for 0-D simulations are now practical for full 3-D engine
simulations complete with moving pistons and valves. With innovative approaches to relieving the
bottleneck in chemistry calculations, predictive engine simulation is now a reality.

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Figure 3: Advanced chemistry solution methods change what is possible for engine simulations.

Reference

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“Predicting Simulation of Combustion Engine Performance in an Evolving Fuel Environment,” US DOE Sandia

White Paper, submitted by Robert W. Carling, February 25, 2010.