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Model reduction in fluid mechanics: a short tutorial

Event Type: 
Date and Time: 
Friday, January 13, 2017 - 16:15
CTR Conference Room 103
Event Sponsor: 
Parviz Moin, Director of Center for Turbulence Research
Aaron Towne, CTR Postdoctoral Fellow, Stanford University

Reduced-order models that capture the essential features of turbulent flows can be used to gain insight into the flow physics, predict quantities of interest, and provide a handle for flow-control efforts.  This talk will compare and contrast a selection of empirical (data-based) and non-empirical (equation-based) model-reduction methods, including several variants of proper orthogonal decomposition, dynamic mode decomposition, resolvent analysis, and balanced truncation.  The hope is that this introduction will help listeners interpret the work of others and select appropriate approaches for their own work.

Aaron Towne is a postdoctoral fellow in the Center for Turbulence Research.  He received his B.S. in Engineering Mechanics from the University of Wisconsin-Madison and his M.S. and Ph.D. in Mechanical Engineering from the California Institute of Technology.  His research interests include aeroacoustics, reduced-order modeling, and flow instability.