DOESciDAC ReviewOffice of Science
ENERGY Science with DIGITAL Combustors
About 80% of the total energy used each year is consumed by combustion in machines such as gasoline and diesel-powered vehicles, jet planes, and electric power plants. Worldwide, fossil fuels add more than twenty five billion tons of carbon dioxide to the atmosphere every year, along with vast quantities of other pollutants. Even modest gains in the efficiency of combustion translate into significant energy savings, reduced pollution, and decreased reliance on foreign energy sources.

Scientists working on Office of Science–funded "Terascale High-Fidelity Simulations of Turbulent Combustion with Detailed Chemistry (TSTC)" and other projects are exploring new ways to burn fuels that will improve combustion efficiency while controlling noxious emissions. Results derived from computer simulations (such as the scalar dissipation rate map indicating the local mixing intensity, depicted in figure 1) enable researchers to digitally evaluate new combustion technology without resorting to costly and timeconsuming prototyping.

Figure 1. A volume rendering of scalar dissipation rates indicative of the local mixing intensity in a temporal plane jet flame. High values in red, medium in yellow, and lower values in blue. The scalar dissipation rate shows a complex, turbulent structure and exhibits a wide dynamic range. The highest scalar dissipation rates exist in thin, highly intermittent layers. CREDIT: K. L. Ma, H. Akiba and H. Yu, University of California - Davis and E. Hawkes, Sandia National Laboratories
Large-scale simulations have proven useful in the development of engines for burning lean mixtures, in which the ratio of fuel to air is lower than the chemically optimal ratio. Reducing the fuel-to-air ratio results in lower maximum temperatures and decreases emission of nitrogen oxides, hydrocarbons, and carbon monoxide. The homogenouscharge compression ignition (HCCI) process is an example of advanced lean-burn technology, promising both high efficiency and low emissions by compressing a lean, premixed fuel-air mixture until it ignites spontaneously in many separate locations (figure 2). One challenge posed by HCCI combustion is the prevention of engine knock, a rapid rise of combustion pressures that may occur at high loads in engines and can often lead to engine damage. One potential method of eliminating knock is to introduce thermal or mixture variations in the engine cylinder to produce the desired heat release rate. To model and improve the performance of such an engine, researchers must be able to understand the propagation of autoignition through a thermally stratified mixture.
Figure 2. SciDAC researchers are actively exploring the science underlying novel engine concepts like homogenous-charge compression ignition (HCCI), shown here in contrast to conventional gasoline and diesel engine designs. In this process, a lean fuel-air mixture is heated by compression and ignites spontaneously in many places. Researchers hope that such engines will provide the high efficiency of diesel engines without the associated emissions. CREDIT: Illustration: A. Tovey
Combustion involves complex interactions between chemistry and turbulent fluid flow (sidebar "Physics of Combustion," p45). State-of-the-art research draws on three complementary parts: theory, computer simulation, and experiment. Theoretical analysis provides the basic framework for understanding what is happening at a microscopic level. Computer simulations enable researchers to explore how the microscopic relations that govern the delicate balance between molecular diffusion and reaction lead to often surprising large-scale (macroscopic) behavior. In the case of combustion for example, the underlying phenomena include turbulent fluid flow and potentially thousands of chemical reactions among hundreds of chemical species. Understanding turbulent flow is critical to proper design. Efficient combustion occurs when there is sufficient turbulence to thoroughly mix the air and fuel, but not so much that the combustion flame is prematurely extinguished. Computer simulations provide a way of studying the effect of turbulence inside the combustion chamber on chemical reactions, and vice versa.
Despite the power of modern computers, they cannot yet completely simulate a combustion chamber over the entire relevant span of length scales, from chemical reactions in the smallest, submillimeter whorls of turbulent flow to the many-centimeter dimensions of the chamber itself. The calculations must span similarly wide ranges in time. Recent advances in supercomputing power together with high-order accurate scalable algorithms have enabled researchers to address fundamental combustion questions with unprecedented realism using Direct Numerical Simulation (DNS). DNS is a high-fidelity simulation approach that numerically resolves all of the relevant fluid and chemical scales and addresses fundamental combustion questions with unprecedented realism. DNS is the gold standard in computational fluid dynamics (CFD) and can provide complete spatial and temporal information for simple canonical configurations, such as the model systems encountered in laboratory-scale experiments. Scientists can use this information to determine the causal relationships between the chemical and physical events occurring during combustion. While experimentation provides partial information under realistic conditions, DNS uses the power of the world's largest supercomputers to provide complete information beginning to approach realistic conditions. DNS can test how accurately various approximations capture the average behavior of the combustion process for engineering models. These engineering models can then be used in more conventional CFD codes to calculate the behavior of the complete combustion chamber under various conditions. Finally, researchers can cross-check the results of these calculations with the behavior of experimental chambers, to ensure that all necessary features have been included in the modeling. In addition to validating these approximate models, the detailed microscopic description of the combustion process yielded by DNS provides a stringent test of theoretical models in a way experiments cannot.
The SciDAC program has funded two projects to study the interactions between the fluid flow and chemical reactions that constitute combustion. The thrust of this article concerns the TSTC project, which is led by investigators Dr. Hong Im of the University of Michigan, Dr. Jacqueline Chen of Sandia National Laboratories (SNL), Dr. Christopher Rutland of the University of Wisconsin Madison, and Dr. Arnaud Trouvé of the University of Maryland. Involving multiple institutions and researchers, the TSTC team has adapted existing code, developed at SNL, to incorporate improved algorithms for treatment of numerical boundary conditions. TSTC researchers have also included important new physical models to simulate spray combustion, as well as soot and thermal radiation interactions.
TSTC workers cooperate with scientists from other SciDAC projects including the Computational Facility for Reacting Flow Science (CFRFS; see sidebar "Computational Facility for Reacting Flow Science," p48), as well as other SciDACsupported researchers like Dr. John Bell of Lawrence Berkeley National Laboratory (LBNL; see "Simulating Turbulent Flames," p25). Other DOE programs support exploration of engineering models such as the Large Eddy Simulation (LES; see sidebar "Engineering Models," p50).
Physics of Combustion
What makes the simulation of combustion so difficult? For one thing, the gas flow in any modern engine is highly turbulent. This means that the gas, instead of flowing along smooth, predictable trajectories, forms into swirling eddies, which in turn spawn smaller eddies down to very small length scales. This swirling action is important to mix the fuel and air for efficient burning. The chaotic nature of this fluid motion is one of the most poorly understood problems of classical physics.
Within the turbulent flow, other complicated events occur. In each small volume of the fluid there are numerous chemical species, and each can potentially undergo many possible chemical reactions. Computer modeling must track the changing concentrations of each of these species as combustion proceeds. Researchers frequently simplify the chemistry, replacing the detailed chemistry with more general reaction systems.
Individually, both chemistry and turbulence are challenging problems. Adding to the complexity, in a burning mixture the chemistry and the turbulence are constantly interacting. The turbulent flow stirs the mixture, creating new conditions. The molecules also diffuse rapidly within the gas, with lighter species like hydrogen moving faster than heavier ones. At the same time, the energy released by combustion heats the gas, changing the flow further.
To accurately model these complex turbulence-chemistry interactions requires high resolution in space and time, as well as wide dynamic range. These simulations must also be advanced over long periods of time to achieve the statistical stationarity required to test models. A quite tractable simulation can very quickly grow into a problem requiring terascale or petascale computers. Developing petascale computing capabilities for open science is a major goal of the SciDAC program.
Advanced Computing
Only in recent years has DNS begun to approach the goal of simulating full-scale, three-dimensional combustion. One of the most powerful examples of this effort is the S3D solver developed at SNL. S3D solves the full compressible Navier-Stokes equations that describe the conservation of mass, momentum, and energy, and laws of gas behavior, while simultaneously tracking the evolution of reactive species on a rectangular mesh. It uses the message passing interface (MPI) to efficiently distribute the calculation among parallel processors, and is built on a hierarchical, modular structure.

With support from the SciDAC Scientific Application Program (SAP), combustion researchers at SNL–together with computer scientists at the National Energy Research Scientific Computing (NERSC) Center and the National Center for Computational Sciences (NCCS) at Oak Ridge National Laboratory (ORNL)–optimized and rewrote several important modules in S3D, improving performance by about 50% on scalar architectures. The adaptations also permit large simulations on vector machines like the Cray X1E. These efforts have dramatically improved the ability of the S3D software to run efficiently on a variety of terascale computing platforms (figure 3). Dr. Chen's group is currently working closely with computer scientists at NCCS/ORNL on scaling S3D to petascale machines.

Figure 3. S3D software has been modified to run efficiently on a variety of processing platforms, and to maintain its performance when thousands of processors are run in parallel.
CREDIT: Illustration: A. Tovey
TSTC researchers have developed special code modules to include additional important physical effects. For example, simulating the injection of fuel into a combustion chamber as a spray requires accounting for the evaporation of the fuel droplets, as well as the entrainment of the gas by the droplets. Dr. Rutland's team has developed tools for incorporating these effects into simulations (sidebar "Simulating Sprays," p46).
In addition to the traditional mechanisms of conduction and convection, researchers are recognizing the increasing importance of including heat transfer through radiation. Dr. Im, Dr. Trouvé, and their collaborators are addressing soot, radiation, and the interaction between the two (sidebar "Soot and Radiation," p47).
Simulating Sprays
In diesel engines, droplets of liquid fuel are sprayed directly into the hot combustion chamber, where they evaporate and form a flame. Automobile engines are "heading towards direct injection" as well, says Dr. Chris Rutland of the University of Wisconsin (UW) at Madison.

With support from several combustion research projects, the UW researchers have simulated the injection of as many as one hundred thousand droplets in a Direct Numerical Simulation (DNS). They track the shrinking size of the droplets so that they can quantify the evaporation rate as well as the transfer of momentum to the fluid. However, they model the droplets as simple point particles moving through the computational grid, simplifying the complex fluid flow around each droplet.

The researchers designed simulation models of the injection of n-heptane. This seven-carbon molecule is a primary component of diesel fuel, Dr. Rutland says, but "the complexity in chemistry [grows] roughly with the number of carbon atoms" because of the larger number of species and reactions in the flame. Still, capturing the detailed evaporation of droplets is critical to describing the cooling of the gas near the jet tip. Because of this cooling, ignition tends to occur in a sheath surrounding the jet (figure 4).

Figure 4. Two-dimensional simulations of a jet spray show the cooling caused by evaporation near the tip of the jet (indicated by cooler colors), causing ignition to start near the edges of the jet. The black line shows the position where the fuel and air are in stoichiometric ratio. CREDIT: C. Rutland, University of Wisconsin - Madison
Incorporating the physics of sprays into large, three-dimensional DNS codes will enable researchers to better understand the behavior of diesel engines, as well as direct-injection gasoline engines. Engineers believe this understanding should help in designing cleaner and more efficient engines.
An important challenge in combustion simulation is the wide range of time scales over which important chemical reactions occur, from nanoseconds to milliseconds. The large discrepancy in time scales, known as stiffness, can drastically degrade the efficiency of calculations, since a simulation that can accurately capture the chemical activity will require a great number of steps to describe the slowly evolving flow. Researchers at Princeton University are developing non-stiff, accurate, efficient models for chemical reactions using an automated mechanism generation software library. Another approach is to modify the algorithms for calculating the time evolution by integrating the chemical sources implicitly. The CFRFS has also independently developed methods for reducing stiffness (sidebar "Computational Facility for Reacting Flow Science," p48).
An important method for focusing computational resources where they are needed is adaptive mesh refinement (AMR). In this technique, the computational mesh is made finer in the small regions where the gas properties are varying rapidly with position. CFRFS researchers have implemented AMR on their platform as well.
AMR is most effective when combustion occurs in flamelets, thin localized sheets, as in the simulations of Dr. Bell and his coworkers ("Simulating Turbulent Flames," p25). In contrast, Dr. Chen's group uses simulations to probe the "thin reaction zones" regime, where the turbulence and flame scales are comparable and occupy a significant fraction of the computational domain, making AMR less effective.
The large, complex datasets that emerge from simulations of turbulent combustion make data management and extraction of useful information a challenge. Combustion researchers have worked closely with computer scientists and applied mathematicians to explore new ways to manage, mine, and visualize the terabytes of data ("From Data to Discovery," p28). In collaboration with researchers from the University of California–Davis led by Dr. Kwan-Liu Ma, TSTC researchers have been exploring new ways to simultaneously visualize multiple variables from large datasets. The continuing efforts toward improved visualization draw on technical illustration techniques and methods such as animation, slicing, and user control of data selection to provide a real-time, interactive platform with which researchers can explore their results. Volume rendering, like that shown in figure 1, enables researchers to easily identify regions of high scalar dissipation rate.
Soot and Radiation
Dr. H. Im, Dr. A Trouvé, and collaborators have included two additional physical phenomena in flame simulation with the S3D code: thermal radiation and soot formation.

Anyone can see that the hot gases of a flame emit radiation in the form of visible light. More important for combustion researchers, however, is the infrared radiation they emit, which can transfer energy over long distances. In contrast, simulations traditionally include local heat transfer by convection and conduction.

The researchers developed two different models for radiation. The discrete ordinate method (DOM) is easily implemented because it directly exploits the grid structure. The discrete transfer method (DTM) uses a raytracing algorithm, and then determines the radiation power at each grid point by a local projection operation. Although the models are established, they have not been widely incorporated into DNS calculations.

Figure 5. TSTC researchers have simulated turbulent sooting non-premixed ethylene-air flames in an opposing jet geometry. Images from left to right correspond to vorticity magnitude, temperature, and soot volume fraction. CREDIT: H. G. Im, University of Michigan
The team also included a model for the formation of soot, which occurs due to the aggregation of incompletely burned fuel. This aggregation begins with a few molecules, and can grow to the large, black particles often observed in truck exhaust. However, small, invisible soot particles are of increasing concern for their potential effects on both health and climate. The virtually endless variety of sizes of soot particles precludes any direct tracking as is done for detailed chemical interactions. Instead, researchers track the total mass fraction of soot and the density of soot particles. The ready absorption of infrared radiation by soot particles causes local heating. This interdependence of radiation and soot behavior is the reason the two phenomena must be considered together in models. Studies of turbulent non-premixed flames showed that tracking of the local flow and chemistry is critical for accurate prediction of soot formation.
One challenge in analyzing HCCI lies in tracking the ignition, propagation, and extinction of local ignition fronts. Researchers have adapted the FastBit indexing techniques (sidebar "FastBit: Indexing for Fast Searches," p34) developed by the Scientific Data Management (SDM) Integrated Software Infrastructure Center (ISIC) to detect and track these local features. They do this by providing a definition of an ignition front based on local conditions such as temperature and chemical composition, which then allows them to transform the challenge of describing the complex autoigniting mixture into one of tracking individual ignition features (figure 3, p32). Sophisticated rules identify critical points that provide topological information about the turbulent eddies and how they relate to the temperature and reactive species. By extracting these critical data points from otherwise continuous data, combustion researchers will be able to skeletonize the data, retaining only the salient features in an intelligible and unambiguous form. By incorporating information about the persistence of structures in time and by looking over multiple length scales, the technique should identify and track intermittent events of extinction and reignition.
Combustion Insights
Combustion occurs under many different conditions, such as with or without premixing of the air and fuel, under various concentrations and chemical compositions, and using continuous or repetitive ignition. The expanded capability of the S3D platform has allowed TSTC scientists and other researchers to simulate more realistic problems, and has thereby provided insight into a variety of combustion conditions.
In the context of the HCCI process, researchers have learned important details about how the ignition front propagates under lean conditions. During traditional fuel-rich operation, an ignited flame propagates by deflagration, the process in which the heat of combustion ignites nearby regions in a steadily propagating front. The motion of the front involves significant molecular transport. A different set of conditions could produce a flame front that appears similar, but on a microscopic scale involves many sequential, independent ignition events. Using DNS, researchers at SNL discovered that the local speed of the front indicates which of these phenomena is occurring. When the temperature is made to vary with position to spread the ignition out over time (figure 6) to avoid excessive pressure rise rates, they showed that both types of fronts are present. Sequential ignition is prominent when the temperature is relatively uniform, while deflagration predominates when the temperature variation is greater. This sort of microscopic information is virtually impossible to glean from experimental studies, and can guide engine researchers to devise optimal strategies for mixture preparation to control the rate of pressure rise.
Computational Facility for Reacting Flow Science
Under the direction of Dr. Habib Najm of Sandia National Laboratories, the Computational Facility for Reacting Flow Science (CFRFS) project has been building a flexible modular platform for simulating combustion and the problems of reactive fluids. In particular, researchers have built tools for high-order adaptive mesh refinement (AMR) and chemical reduction within the framework of the Common Component Architecture (CCA), which was developed by SciDAC's Center for Component Technology for Terascale Simulation Software (CCTTSS). This modular platform supports various types of reacting flows, including combustion, climate studies, and other fields.
The primary work of this group is to provide a modular structure for combustion compatible with the CCA. One aspect of this is a library that allows parallel implementation of adaptive mesh refinement (a complementary use of adaptive mesh refinement is discussed in "Simulating Turbulent Flames," p25).
Another CFRFS thrust is the automated reduction of chemical complexity in reacting flows. Researchers are using computational singular perturbation (CSP) theory to eliminate unimportant reactions. "Outside of the flame front, most of the chemistry is dormant or exhausted," Dr. Najm says, allowing researchers to simplify the chemical modeling almost everywhere in the simulation.
Achieving this goal requires an automated, adaptive chemical reduction scheme, crudely analogous to the adaptive mesh refinement in the spatial domain. The idea is to render the chemical system with "as much complexity as needed and no more." The research team has explored the practicality of this idea in simplified systems, and is evaluating its use in full combustion simulations.

Figure 6. In these snapshots from two-dimensional simulations of HCCI combustion, the initial temperature of the hydrogen-air charge varies from place to place, encouraging earlier ignition in hotter regions. Heat release is shown on a rainbow scale, varying from blue (in the regions of lowest heat release) through red to white. In the upper left panel, turbulence is suppressed, so combustion propagates steadily away from the initial ignition sites. In the upper right panel, turbulent flow speeds combustion by mixing the fluid, but also disrupts the propagation of the combustion front. The effect is less pronounced in the lower panels, where both the length scale of the temperature fluctuation is smaller by a factor of four, and the size of the simulated volume is reduced by the same factor. CREDIT: E. Hawkes et al., 2006 Combust. Flame 145 145-159
  Researchers at Stanford University used these data to validate a flamelet model for combustion. Their model relied on the results for the diffusion of scalar quantities in the turbulent system. Because of this diffusion, detailed comparison between the results of their model and the DNS simulation showed a much better agreement than a traditional multi-zone model which includes pressure coupling between zones but neglects diffusive transport (figure 7). In this case, the DNS calculations provide the detailed information needed to test a specific microscopic theory of the combustion process.

Lean premixed combustion is also found in turbines for power generation. The laboratory turbulent Bunsen burner configuration (figure 8) is useful to study the effect of turbulence on flame structure and propagation in parameter regimes relevant to stationary gas turbines. Lean premixed combustion has the advantage of higher thermal efficiency and low NOx emissions. Lean flames tend to be broader and propagate more slowly. Hence, these devices operate at higher turbulence intensity relative to the flame propagation speed. This system of combustion is known as the thin reaction zones regime, where small scale turbulence can penetrate the leading edge of the flame known as the preheat zone, but not the reaction zone. Thin reaction zones combustion has not been well understood or modeled effectively in the past. Researchers only recently performed a three-dimensional simulation of a flame in this regime for the first time. These simulations clarify the effect of the small-scale turbulence on the flame structure that can affect the turbulent burning rate and flame stability near the lean limit. A new mathematical formulation to describe the upstream boundary conditions developed by TSTC researchers was used to prevent spurious pressure waves as turbulence is introduced into the computational domain.

To simplify the chemistry of the methane-air system, combustion scientists worked closely with engineers at Princeton University to systematically eliminate chemical reactions that are unimportant under lean conditions and to reduce the chemical stiffness. CFRFS researchers have also been developing chemical reduction software (sidebar "Computational Facility for Reacting Flow Science," p48). They found that turbulent mixing increased the thickness of the flame with important consequences for the overall turbulent propagation speed.

In some cases fuel and air are introduced separately into the combustion chamber, and turbulent flow is needed to quickly mix the reactants. Jet aircraft employ such "non-premixed" combustion for safety reasons, and it occurs in direct injection diesel and gasoline engines as well. In recognition of the growing power of DNS and the S3D platform, combustion chemistry researchers Dr. Chen and Dr. Evatt Hawkes received an award of computing resources under the 2005 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program to explore this regime. This work is the largest ever simulation of turbulent combustion using detailed chemistry, with over half a billion grid points used to transport fifteen variables. The results showed that, in contrast to the assumptions of current models, the mixing process of reactive species is not analogous to the dissipation of kinetic energy from the turbulence field. This is due to the strong interplay between reaction and molecular diffusion and to the large differences in transport properties of the species. The results also gave hints of new mechanisms for reignition subsequent to local extinction (sidebar "INCITE Project," p51).

Figure 7. The stratification of the premixed HCCI charge into regions of different temperature can spread the spontaneous ignition in time, making the heat release less abrupt. When the temperature variation imposed on a simulation is large, like that in figure 6, the spreading is significant. A flamelet-based theory successfully described the resulting heat release much better than a competing multi-zone model.
CREDIT: Illustration: A Tovey Source: D. J. Cook, H. Pitsch, J. H. Chen and E. R. Hawkes
Cooling effects near the combustion chamber wall can strongly influence the flame. Although this cooling can be useful by helping to stratify the charge in an HCCI device, under lean conditions the cooling may become excessive. Researchers led by the University of Maryland group simulated a two-dimensional ethylene-air jet, and found flame extinction near the walls. Such extinction is a dominant mechanism for emission of unburned hydrocarbons. The importance of walls will be even more crucial in compact microcombustion chambers that are currently under study by the SNL group and collaborators at the University of Trondheim.
Figure 8. TSTC researchers have simulated the combustion of premixed gases in an elongated Bunsen geometry, as illustrated here. The left image corresponds to temperature, and the right image shows flame surface location of maximum heat release. CREDIT: R. Sankaran, E. R. Hawkes, J. H. Chen, T. Lu and C. K. La
Engineering Models
Direct Numerical Simulations of combustion have advanced tremendously in recent years, and in some cases can simulate three-dimensional regions centimeters in size ("Simulating Turbulent Flames," p25). However, it is still impossible to use DNS on the scale of a complete combustor, for example to select the best geometry for a reaction chamber. Small details in the chamber can have an important effect on the performance, such as by inducing additional turbulent mixing at the inlet valves.

Instead, DNS accurately captures the finest-scale details of the combustion over a reasonably large volume, which can then be compared with theoretical combustion models. In addition, the simulations are used to validate large-scale engineering models of the combustion process, in which finer-scale spatial or temporal details of the flow are replaced by averages or smoothed representations. Two important techniques for doing this are Reynolds Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES).

RANS creates a model for the larger problem by averaging the local quantities entered into the full Navier-Stokes equations describing fluid flow. In LES, the largest eddies are directly simulated, while eddies smaller than the grid are modeled.

Figure 9. Large Eddy Simulation (LES) of a swirling premixed flame in a laboratory-scale annular combustor. The left side shows the instantaneous velocity field, while the right side shows the time-averaged velocity field.
CREDIT: J. C. Oefelein, Sandia National Laboratories
Optimizing the DNS S3D Code
Direct Numerical Simulation (DNS) is an essential tool for understanding the physics of turbulence. The S3D code eveloped at Sandia National Laboratories (SNL) is a massively parallel DNS solver for turbulent reacting flows and includes multiple physical and chemical aspects such as detailed chemistry and molecular transport.
In the past year, Dr. Ramanan Sankaran (SNL), Dr. Evatt Hawkes (SNL), Dr. Mark Fahey (Oak Ridge National Laboratory; ORNL) and Dr. David Skinner (National Energy Research Scientific Computing Center; NERSC) optimized several key kernels in S3D for both scalar and vector architectures. As a result of the optimization, there was a 45% improvement in performance on NERSC's IBM SP, nicknamed "Seaborg". Vectorization of S3D resulted in a ten-fold improvement in performance on ORNL's Cray X1E, called "Phoenix". Additionally, S3D has been shown to scale remarkably well on several different platforms (figure 3, p45). Notably, S3D has 90% parallel efficiency on 5120 Cray XT3 processors at ORNL.
Writer: Dr. Ramanan Sankaran, Post-Doc, Combustion Research Facility, Sandia National Laboratories
Future Directions & Summary
SciDAC programs are vastly improving the power of DNS of turbulent combustion, as part of a broader program to improve the efficiency and reduce the environmental impact of these critical technologies. Together with experiments, DNS allows researchers to discern the most important factors that affect the behavior of combustion. For example, DNS clarifies the interactions between chemistry and turbulence, which are critical to getting the most out of modern engine concepts such as HCCI.
Benchmark DNS simulations also provide highly detailed data to test models for engineering simulations. Such engineering analyses are large enough to include the details of engine geometry, such as chamber shape, valve design, and so forth. However, these calculations must approximate the behavior of the reacting gases (sidebar "Engineering Models," p50). DNS allows researchers to validate these approximations so that they can best design the entire system and confirm microscopic theoretical pictures for the key processes that govern combustion.
INCITE Project
The Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program encourages researchers to address some of the grandest challenges in simulation. In 2005, researchers built on the success of the TSTC and and other Office of Science programs to directly simulate the first 3D turbulent non-premixed H2-CO-N2 flame with detailed chemistry aimed at studying the mechanisms of extinction and reignition. Such nonpremixed combustion occurs in aircraft engines and in direct-injection internal combustion engines. The flow must be highly turbulent to ensure adequate mixing of the fuel and the oxidizer. However, this same turbulence also increases the chances for local extinction of the flame when turbulent strain produces mixing rates so large that the reactions cannot keep up.

The INCITE-supported simulations clarified the process of mixing, which is central to the combustion process. In most large-scale engineering models of combustion, scalar quantities such as gas temperature and composition are presumed to mix at the same rate as vector properties of the fluid flow, such as momentum. For non-reactive scalars (those that do not participate in the chemical reactions of combustion) the simulations validate this assumption. However, the researchers found that for light species such as molecular and atomic hydrogen, as well as for scalar properties affected by the evolving chemical environment, the mixing time differed by as much as a factor of three.

Turbulence is needed to properly mix reactants for combustion. However, if the turbulence is too great it can separate two adjacent volumes of fluid, one burning, the other containing unreacted material, before the flame can propagate between them. In a steady flame like those found in turbines, this can lead to blowout. Under the right conditions, however, the mixture can reignite. Understanding the detailed processes of extinction and reignition is critical to modeling combustion in aircraft engines. The researchers have identified important new features of the reignition process, and continue to explore the 30 terabytes of data that emerged from these simulations with help from computer scientists.

Figure 10. Using a large computer allocation provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program, researchers performed the largest Direct Numerical Simulation (DNS) of non-premixed turbulent combustion to date. This volume from the simulation of a H2-CO flame shows the vorticity from high to low as red, yellow, and blue. CREDIT: H. Akiba and K. L. Ma, University of California - Davis
As computers become more powerful and researchers continually enhance their code, numerical simulations of combustion will become ever more detailed and physically realistic. Although the dream of simulating an entire combustion chamber is still elusive, current simulations give critical validation to the understanding of what governs combustion behavior and how best to describe it in engineering simulations. In light of the economic and environmental impact of combustion, the importance of this research is enormous. To put it into perspective, a 50% increase in efficiency of automobiles would result in over 20% savings in the nation's petroleum consumption for transportation. Combustion research supported by SciDAC and other programs will help to realize such rewarding accomplishments in the future.
Writer: Don Monroe, Ph.D.
Further reading
TSTC Project
CFRFS Projectt
D. Cook, H. Pitsch, J. H. Chen, and E. R. Hawkes. (in press). Flamelet based modeling of autoignition with thermal inhomogeneities for application to HCCI engines. Proc. Combustion Institute.
E. R. Hawkes, R. Sankaran, P. P. Pebay, and J. H. Chen. 2006. Direct Numerical Simulation of ignition front propagation in a constant volume with temperature inhomogeneities: part II, parametric study. Combust. Flame 145 145-159.
E. R. Hawkes, R. Sankaran, J. C. Sutherland, and J. H. Chen. 2006. Scalar mixing in Direct Numerical Simulations of temporally evolving nonpremixed plane jet flames with skeletal CO-H2 kinetics. Proc. Combustion Institute 31.
T. F. Lu and C. K. Law. 2005. A directed relation graph method for mechanism reduction. Proc. Combustion Institute 30 1333-1341.
R. Sankaran, E. R. Hawkes, J. H. Chen, T. Lu, and C. K. Law. (in press). Structure of a spatially developing lean methane-air turbulent Bunsen flame. Proc. Combustion Institute.