Data-driven descriptions of linear & nonlinear interactions in wall turbulence

Abstract: Significant recent progress has been made in flow modeling using both equation-driven and data-driven techniques. We focus here on the intersection of these two approaches, using data to complete the details of known flow dynamics. We utilize the classical approaches and tools of the modern day – theoretical analysis, data-driven methods and machine learning tools – to illuminate features responsible for the sustenance of turbulence associated with nonlinear interactions in the Navier-Stokes equations. Focusing on a spatio-temporal representation of turbulence near walls – an omnipresent phenomenon in large-scale transport and transportation – we identify and quantify key scale interactions. Methods to obtain data-driven representations of both linear and nonlinear dynamics will be discussed, along with some implications for the modeling of wall turbulence. The work has benefited from funding by the US ONR, ARO and AFOSR over a period of years, which is gratefully acknowledged.

Bio: Beverley J. McKeon is Professor of Mechanical Engineering at Stanford, effective January 1, 2023. Previously she was the Theodore von Karman Professor of Aeronautics at the Graduate Aerospace Laboratories at Caltech (GALCIT) and former Deputy Chair of the Division of Engineering & Applied Science. She received her B.A., M.A. and M.Eng. from the University of Cambridge in the United Kingdom, and an M.A. and Ph.D. in Mechanical and Aerospace Engineering from Princeton University under the supervision of Lex Smits. She completed postdoctoral research and a Royal Society Dorothy Hodgkin Fellowship at Imperial College London before starting at Caltech in 2006. Her research interests include interdisciplinary approaches to manipulation of boundary layer flows using morphing surfaces, fundamental investigations of wall turbulence and the influence of the wall at high Reynolds number, the development of resolvent analysis for modeling turbulent flows, and assimilation of experimental data for efficient low-order flow modeling.Prof. McKeon is a Fellow of the APS and the AIAA and the recipient of a Vannevar Bush Faculty Fellowship from the DoD in 2017, the Presidential Early Career Award (PECASE) in 2009 and an NSF CAREER Award in 2008 as well as Caltech’s Shair Program Diversity Award, Graduate Student Council Excellence in Mentoring Award and Northrop Grumman Prize for Excellence in Teaching. She currently serves as co-Lead Editor of Physical Review Fluids, as Physical Sciences co-captain on the National Academies Decadal Survey on Biological and Physical Sciences Research in Space 2023-32, and on the editorial board of the Annual Review of Fluid Mechanics. She is the Past Chair of the US National Committee on Theoretical and Applied Mechanics.