CDS&E: Data Management and Visualization in Petascale Turbulent Combustion Simulation

点击翻译按钮获取中文摘要

CBET-1250171PI: Peyman Givi, Univ. of PittsburghThis award provides funding for developments of (1) a robust computational method for petascale simulationof turbulent combustion, (2) a scalable data management system for such simulations and (3) a systematicvisual analysis of the generated data. The computational method will be based on the filtered density function(FDF) methodology for large eddy simulation (LES) of complex turbulent flames. The simulation willbe based on a new algorithm, termed ?irregularly portioned Lagrangian Monte Carlo-Finite Difference?(IPLMCFD) which facilitate FDF simulations on massively parallel, up to petascale platforms. Data managementwill be provided by addressing research challenges in management of annotations, managementof workflows and data archiving. Effective data visualization and analysis will be conducted through amachine learning ?feature-extraction? approach. This work crosses the disciplines of engineering and computerscience and expands the state-of-the-art in high fidelity predictions of turbulent reacting flows. At theconclusion of the work, an open source LES code will be provided for use by the public.If successful, the results of this research will have a significant impact in combustion, both in gas-turbineindustry and in government. It is firmly believed that LES will constitute the primary means of predictionsfor future design and manufacturing of combustion systems. Having it coupled with robust and versatile datamanagement and visualization capabilities will be useful for both basic and applied research purposes. Someof the other broader impacts are through involvement of undergraduate students in research and attractingthem to graduate school, K-12 outreach, involvement of high school students in research, and recruitmentof students from minority and under-represented groups.