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DTSTART:19700308T020000
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DTSTART:19701101T020000
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DTSTAMP:20210916T132450Z
LOCATION:Ernesto Bertarelli
DTSTART;TZID=Europe/Stockholm:20210706T143000
DTEND;TZID=Europe/Stockholm:20210706T150000
UID:submissions.pasc-conference.org_PASC21_sess138_msa387@linklings.com
SUMMARY:UQ, Optimization, and Multifidelity Models for Simulations of Turb
 ulent Flows
DESCRIPTION:Minisymposium\n\nUQ, Optimization, and Multifidelity Models fo
 r Simulations of Turbulent Flows\n\nRezaeiravesh\n\nSeveral challenges are
  involved in scale-resolving simulations of wall-bounded turbulent flows w
 hich appear in many engineering applications. The challenges include high 
 computational cost of the simulations especially at high Reynolds numbers,
  and also the uncertainties in the simulations outputs due to various fact
 ors. In this regard, the present talk discusses our recent progress on thr
 ee connected subjects: i) uncertainty quantification (UQ) and sensitivity 
 analysis for parametric and time-averaging uncertainties, ii) Bayesian opt
 imization based on Gaussian processes, and iii) multifidelity models (MFMs
 ) for UQ and optimization in turbulent flows. In constructing a multifidel
 ity model for an “outer-loop” problem, highest predictive accu
 racy for a given computational budget is targeted. We discuss a class of M
 FMs which are consistent with the hierarchy of approaches for numerical mo
 deling of turbulence and can also handle different uncertainties. Using a 
 limited number of realizations (mostly by running low-fidelity simulations
 ), the MFM is constructed within a Bayesian framework. It can then be empl
 oyed for uncertainty propagation, predictions over the input space, and op
 timization of design parameters- at a lower cost.\n\nDomain: CS and Math, 
 Physics, Engineering
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