Principal Investigator: Im, Hong G. [Lead] Institution: University of Michigan Ann Arbor Proposal No: OCI-0904660 Principal Investigator: Trouve, Arnaud C Institution: University of Maryland College Park Proposal No: OCI-0904480 Principal Investigator: Haworth, Daniel C. Institution: Pennsylvania State Univ University Park Proposal No: OCI-0904649 Principal Investigator: Lu, Tianfeng Institution: University of Connecticut Proposal No: OCI-0904771 Principal Investigator: Sankaran, Ramanan Institution: University of Tennessee Knoxville Proposal No: OCI-0904818 Principal Investigator: Ma, Kwan-Liu Institution: University of California-Davis Proposal No: OCI-0905008

This proposal will be awarded using funds made available by the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

Energy efficiency, the environment, and human health can be affected by combustion-generated soot, so controlling soot is a major technological and societal concern. This research is directed toward achieving soot prediction from turbulent combustion by using peta-flop computing. A team of six research groups is working together to develop a peta-flop software package that will capture the physics and chemistry of turbulent sooting flames at an unprecedented level of detail and realism. These research efforts are expected to lead to breakthroughs in our fundamental understanding of many important scientific issues related to energy conversion and pollutant control. The comprehensive software package developed here will allow detailed consideration of gas-phase chemistry, soot formation, and radiative heat transfer phenomena. It will extend a previous teraflop code for direct numerical simulation (DNS) of turbulent combustion by enhancing parallelism at the grid, operator, and equation levels. Other goals include reduced chemical-kinetic mechanisms for soot formation associated with different hydrocarbon fuels; spectrally resolved radiative heat-transfer models for gases and soot particles allowing arbitrary optical thickness; a soot aerosol and transport model based on the combination of sectional and moment methods; multivariate dataset and data-mining software; novel fault tolerance and checkpoint capabilities; in-situ visualization; and automated feature extraction and tracking of limit phenomena such as ignition/extinction in sooting flames. The new simulation capability will be tested in laboratory-scale turbulent flames at high Reynolds and Damköhler numbers.

This collaborative research will enhance the nation?s competitiveness by engaging a new generation of students in multi-disciplinary computational science and engineering. Faculty, students, and the resulting software development will benefit from the interdisciplinary interchange of computer science and domain science necessary to ensure that the code is designed and optimized efficiently. Dissemination of the software will occur through an open-source license. The multi-disciplinary, multi-institutional aspects of the project will naturally lead to a number of opportunities for sponsoring high school and undergraduate student research programs. The activities will also complement and benefit from close collaboration with other research groups worldwide in combustion research as well as in computer science.

National Science Foundation (NSF)
Division of Advanced CyberInfrastructure (ACI)
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Daniel Katz
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University of Michigan Ann Arbor
Ann Arbor
United States
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