Characterizing high-Reynolds number turbulence dynamics using low-Reynolds number flows

Speaker: Dr. Sualeh Khurshid - Massachusetts Institute of Technology
Date: Feb 13, 2023; Time: 10:30 AM Location: UTEB 476

Abstract:

Turbulence is ubiquitous in natural and engineering systems. It can suppress energy loss in fusion reactors, affects stellar formation, has first order effects on processes critically important to society such as mixing of chemicals and pollutants in the atmosphere and oceans, climate dynamics and high-speed flight. It is therefore critically important to develop fundamental understanding of turbulent processes to improve predictive capabilities of turbulent fluid systems. An important hurdle in characterizing turbulent flows is the presence of extreme events, e.g. in dissipation, velocity gradients etc. These events are often very high-dimensional in nature and require large degrees of freedom/grid points to resolve accurately in simulations. The extreme events become stronger at high Reynolds number (Re, parameter characterizing the strength of turbulence) that are characteristic of realistic flows. Therefore, the focus of much of turbulence research has been to simulate very high-Re flows. This is a challenging computational task as the computational work load can grow as steeply as the fourth power of Reynolds number. Direct simulations of complex turbulent flows at realistic conditions currently remain elusive on the largest supercomputers. In this talk, we present a new theoretical perspective on understanding high-Re turbulence using well-resolved simulations at low to moderate-Re, that can be simulated on supercomputers available today. We will show that features of high-Re turbulence can be studied at finite and small values of Re and they are predictive of the infinite-Re limit. The simulations have the finest small-scale resolution in literature and long time-series. A primary focus is on the universality of small-scales and the scaling of extreme events. The consequences of these fundamental insights on modeling approaches, phenomenological and data-driven, in complex turbulent flows will also be discussed. The work also provides a new perspective on computational study of complex systems at very high values of dynamically relevant parameters. 

 Bio:

Sualeh Khurshid is a Computing Innovation Fellow and Postdoctoral Associate in Mechanical Engineering at Massachusetts Institute of Technology. His research is focused on understanding fundamental characteristics of complex turbulent flows in various regimes using direct numerical simulations and theory. His work includes developing high performance simulation codes and appropriate numerical methods to guide the development of reduced order models using phenomenological and data-driven methods. He completed undergraduate programs in Aerospace Engineering and Physics in 2016 and earned his Ph.D. in Aerospace Engineering in 2021 at Texas A&M University.