Bio: Aditya G. Nair joined the Department of Mechanical Engineering at U. Nevada, Reno in August 2020. His research interests are in the areas of computational fluid dynamics, unsteady aerodynamics, high-performance computing, data science and control theory focused on modeling and control of high-dimensional fluid flow physics. He received his Ph.D. in mechanical engineering from the Florida State U. in 2018. Prior to this, he completed his M.S. in mechanical engineering from U. Michigan in 2013 and B.E in mechanical engineering from University of Mumbai in 2011. Following his Ph.D., he served as a post-doctoral research associate in the mechanical engineering department at U. of Washington till July 2020.

Physics-based and data-driven strategies for modeling and control of unsteady fluid flows

Data and network science offer novel perspectives to describe complex dynamics over a web of interactions. The last few years have seen an emergence of such techniques to characterize, model, and control fluid flows. The ability of these approaches to characterize vortical and modal interactions in unsteady fluid flows is essential to understand its complex behavior. Using a simple description of the flow physics on a mathematical graph with weights based on vortical interactions, modal interactions and probabilistic interactions, we can design feedback control techniques to alter flow behavior. We discuss some of the successes and challenges associated with applying this formalism for fluid dynamics.

Zoom information
link: umich.zoom.us/j/92859783250
passcode: 833499

Prof. Nair is being hosted by Prof. Johnsen (Mechanical Engineering).