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Advanced Simulation and Computing: Accelerated Computations, Machine Learning and Uncertainty Quantification for Multiphysics Applications

Gianluca Iaccarino, Stanford University

Jet engines, scramjets, rockets and solar energy receivers have been the focus of a sequence of computational projects at Stanford University. Featuring a combination of computer science and multi-physics simulations, the research is funded by Department of Energy. within the Advanced Simulation and Computing (ASC) Program. A common theme of the applications above is the coupled nature of the physical processes involving turbulent transport, combustion, radiation, compressible fluid mechanics, multiphase flow phenomena, etc. The research portfolio includes not only the engineering models and software tools required for the simulations of the overarching applications, but also innovations in high-performance computing and uncertainty quantification aimed at providing quantitative estimates of the prediction accuracy. This talk will trace back the history of the projects at Stanford and how the initial efforts targeting demonstrations on a fastest supercomputer in 2000 (ASCI White) have evolved to enable the present ensemble simulations on today’s exascale class machines.