This talk will explore several developments that improve upon the efficiency, accuracy, and theoretical understanding of methods for reduced-complexity modeling of systems in fluid mechanics and aerodynamics. First, I will discuss an approach for pseudospectral (resolvent) analysis of shear-driven flows that bypasses traditional numerical discretization and computation. The method assumes that spatial structures arising from optimal energy amplification mechanisms can be closely approximated by wavepackets of a given structure, and solves a low-dimensional optimization problem to find the relevant unknown parameters. It will be demonstrated that this method can be effective for the identification of leading and suboptimal pseudospectral modes in parallel shear flows, including cases where the modes are influenced by one or two boundaries and/or multiple critical layers. Following this, I will discuss modeling of transient phenomena in unsteady aerodynamics. It will be shown that certain phenomena cannot be accurately captured by linear models, even for small-amplitude dynamics. This will motivate the development of nonlinear modeling approaches, which will be applied to a range of classical and contemporary unsteady aerodynamics problems.
Scott Dawson is an assistant professor in the Mechanical, Materials and Aerospace Engineering Department at the Illinois Institute of Technology. Prior to this, he was postdoctoral scholar at the California Institute of Technology, and he completed his Ph.D. in Mechanical and Aerospace Engineering at Princeton University. His research interests include modeling, optimization and control in fluid mechanics, with a particular focus on modeling turbulent shear flows and unsteady aerodynamic systems using both physics-based and data-driven approaches.