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Improved Algorithms Lead to Lab-Scale Combustion Simulations

January 1, 2004


In spite of its fundamental technological importance, our knowledge of basic combustion processes is surprisingly incomplete. Theoretical combustion science is unable to address the complexity of realistic flames, and laboratory measurements are difficult to interpret and often limited in the types of applicable flames or levels of detail they can provide. CRD’s Center for Computational Sciences and Engineering (CCSE) has teamed with LBNL’s Environmental Energy Technologies Division (EETD) to build a high- performance computing solution to flame simulation and analysis that has a unique potential for making dramatic progress in combustion science research.


These methane flame images show exceptional agreement between CCSE’s simulation (left) and experimental data (right).

The CCSE group has created the first detailed simulations of laboratory-scale turbulent premixed flame experiments using 3D time-dependent software accommodating an unprecedented level of detail in terms of chemical fidelity and fluid transport. CCSE and EETD researchers work together to validate the simulations with experimental data, and then probe the computed results for information not easily obtainable from the experiment in any other way. The investigations are focused in two primary areas: how turbulence in the fuel stream affects the local combustion chemistry, and how emissions are formed and released in the product stream. The work has applications for devices ranging from power generators, heating systems, water heaters, stove, ovens and even clothes driers.

Simulation at such a level of detail was impossible just a few years ago. However, algorithmic improvements by DOE-funded applied mathematics groups such as CCSE over the past five years have slashed computational costs for these types of flows by a factor of 10,000. Such savings enable key improvements in the fidelity of the chemical and fluid dynamical descriptions of the flows, to the point that real experiments may now be simulated without ad-hoc engineering models for under-resolved physical processes. However, simulation of practical-scale combustion devices remains an immense undertaking. CCSE has implemented their advanced simulation algorithms on state-of- the-art parallel computing hardware to increase the number of variables available for describing the system from hundreds of thousands, five years ago, to more than a billion today.

The research approach taken by CCSE has explicitly targeted both the temporal and spatial multi-scale aspects of combustion modeling. The group takes advantage of key mathematical characteristics of low-speed flows, common to most combustion applications, to eliminate components of the model relevant only to high-speed scenarios. For low speed flows, these components have little effect on the system dynamics, yet they drive down the simulation efficiency by unnecessarily limiting the maximum numerical time step-size. The integration algorithms are implemented in a set of software tools based on adaptive mesh refinement (AMR), a dynamic grid-based system that automatically allocates computational resources to regions that contain the most interesting detail. The AMR methodology allows one to simultaneously incorporate large-scale effects that stabilize the flame, as well as the very fine scale features of the combustion reaction zone itself.

The detailed solutions computed by CCSE are being validated with experimental data provided by the EETD Combustion Lab. Comparisons include global observables, such as mean flame locations and geometries, as well as statistics of instantaneous flame surface structures. In addition to simply validating the computed solutions however, the research groups probe the massive amounts of data generated by the computation in order to learn more about flame details, such as the localized effects of large and small eddies on the structure of the combustion reaction zone. For example, the distribution of hydrogen atoms in the thermal field is tightly coupled to key chain-branching reactions required to sustain the combustion process itself. The detailed models accurately represent the transport of hydrogen with respect to the other chemical species in the context of this turbulent flow. CCSE is presently using detailed chemistry and transport models containing 20 to 65 chemical species, and hundreds of reactions.

CCSE is now working with EETD researchers to develop statistical measures of the simulation and experimental data so that they can obtain a more quantitative comparison. They are also working to understand the volumes of new simulation data in order to quantitatively characterize how fuel-stream turbulence affects the detailed combustion process.

For more information about the CCSE’s adaptive methodology for low Mach number combustion modeling applications, contact Marc Day at MSDay@lbl.gov or John Bell at JBBell@lbl.gov.

About Computing Sciences at Berkeley Lab

The Lawrence Berkeley National Laboratory (Berkeley Lab) Computing Sciences organization provides the computing and networking resources and expertise critical to advancing the Department of Energy's research missions: developing new energy sources, improving energy efficiency, developing new materials and increasing our understanding of ourselves, our world and our universe.

ESnet, the Energy Sciences Network, provides the high-bandwidth, reliable connections that link scientists at 40 DOE research sites to each other and to experimental facilities and supercomputing centers around the country. The National Energy Research Scientific Computing Center (NERSC) powers the discoveries of 7,000-plus scientists at national laboratories and universities, including those at Berkeley Lab's Computational Research Division (CRD). CRD conducts research and development in mathematical modeling and simulation, algorithm design, data storage, management and analysis, computer system architecture and high-performance software implementation. NERSC and ESnet are Department of Energy Office of Science User Facilities.

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