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Exascale for Energy


Currently 85% of our nation’s energy comes from hydrocarbon combustion, including petroleum, natural gas, and coal (Figure 7). Although there may be long-term alternatives to combustion for some uses, changes in fuels and energy technologies tend to happen gradually (Figure 8). High infrastructure costs suggest that combustion may continue to be the predominant source of energy for the next 30 to 50 years.

U.S. energy sources

Figure 7. Combustion accounts for 85% of the energy used in the United States. Source: LLNL


Historic changes in energy supply

Figure 8. Gradual changes in the U.S. energy supply from 1850 to 2000.
Source: EIA

Transportation is the second largest energy consumer in the U.S., accounting for two-thirds of petroleum usage. Transportation technologies provide opportunities for 25% to 50% improvement in efficiency through strategic technical investments in both advanced fuels and new low-temperature engine concepts. These improvements would result in potential savings of 3 million barrels of oil per day, from the total current U.S. consumption of 20 million barrels.

A 2006 DOE Office of Basic Energy Sciences workshop on Basic Research Needs for Clean and Efficient Combustion of 21st Century Transportation Fuels identified a single, overarching grand challenge: the development of a validated, predictive, multi-scale, combustion modeling capability to optimize the design and operation of evolving fuels in advanced engines for transportation applications.

Concern for energy security is driving the development of alternative fuel sources, such as oil shale, oil sands, syngas, and renewable fuels such as ethanol, biodiesel, and hydrogen. These new fuel sources all have physical and chemical properties that are very different from traditional fuels. New combustion systems, for both stationary power plants and transportation, need to be developed to use these fuels efficiently while meeting strict emissions requirements.

Modeling internal combustion engines is a complex, multi-physics, multi-scale problem. Engine combustion processes involve physical and chemical phenomena that span a wide dynamic range (~109) in spatial and temporal scales, involving hundreds of chemical species and thousands of reactions. The microscopic reaction chemistry affects the development of the macroscopic turbulent flow field in engines, and the change in temperature due to the altered flow dramatically affects the reaction rates. Changes in fuel composition directly affect phenomena at several scales. For example, at microscopic scales, fuel changes affect some reaction rates; at larger scales, changes in bulk liquid properties affect fuel injection and evaporation.

Combustion modeling scales
Figure 9. Multi-scale modeling describes internal combustion engine processes from quantum scales up to device-level, continuum scales.
Source: DOE Exascale Initiative

Understanding how changes at specific scales affect the overall performance of an engine requires very careful coupling across the scales, as well as a wide variety of computational techniques, such as quantum dynamics, molecular dynamics, kinetic Monte Carlo, direct numerical simulation, large eddy simulation, and Reynolds-averaged simulation (Figure 9).

Fuel and engine technologies should be developed together if we want to move them as quickly as possible from the laboratory to the marketplace. This co-develop­ment requires a new approach to engineering research and development: instead of hardware-intensive, experience-based engine design, which is slow and labor intensive, we need a relatively faster, simulation-intensive, science-based design process. High-fidelity multiscale modeling on exascale computers will play a key role in enabling this transition.

Lean premixed burners are one example of a new technology being considered for stationary gas turbines, which provide a significant portion of our electric power generation. Theoretically these burners could operate cleanly and efficiently with a variety of fuels, such as hydrogen, syngas, and ethanol, because of their high thermal efficiency and low emissions of NOx due to lower post-flame gas temperatures. However, the lean fuel mix makes some burners susceptible to flame instability and extinction, emissions of unburned fuel, and large pressure oscillations that can result in poor combustion efficiency, toxic emissions, or even mechanical damage to turbine machinery. An important exception to this trend is the low-swirl burner, which produces a stable flame (see sidebar).

Researchers are only beginning to acquire a fundamental understanding of the dynamics of premixed flame propagation and structure for the variety of different fuels that is required to meet the engineering design goals for lean premixed burners. Exascale computing will play a deciding role in whether we are able to design these types of systems.

Effective design of both power generation and transportation systems will require new computational tools that provide unprecedented levels of chemical and fluid dynamical fidelity. Current engineering practice is based on relatively simple models for turbulence combined with phenomenological models for the interaction of flames with the underlying turbulent flow. Design computations are often restricted to two-dimensional or relatively coarse three-dimensional models with low-fidelity approximations of the chemical kinetics.

A dramatic improvement in fidelity will be required to model the next generation of combustion devices (Figure 10). Theory cannot yet provide detailed flame structures or the progression of ignition in complex fuels, while experimental diagnostics provide only a limited picture of flame dynamics and ignition limits. Numerical simulation, working in concert with theory and experiment, has the potential to address the interplay of fluid mechanics, chemistry, and heat transfer needed to address key combustion design issues.

Combustion breakthroughs enabled by computing

Figure 10. Combustion science breakthroughs enabled by algorithms, applications, and HPC capability.
Source: J. Oefelein and R. Barlow, SNL


The grand challenge is to develop a validated, predictive, multiscale, combustion modeling capability that can optimize the design and operation of evolving fuels in advanced engines and power plants. Using exascale computing systems, thousands of design iterations—each corresponding to a high-fidelity multiscale simulation—could accelerate the optimization and implementation of new technologies.

Other scientific challenges related to combustion include capturing and using the energy currently dissipated as waste heat, and capturing and storing the carbon dioxide released by combustion to help stop global warming. Computational simulations are already playing a key role in both efforts, as described in the sidebars on thermoelectrics and carbon sequestration.


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