Past Event: Oden Institute Seminar

Optimization and Learning Algorithms for Survival and Schooling Hydrodynamics

Petros Koumoutsakos , Professor, Computational Science, ETH Zurich

Abstract

The aqueous environment of natural swimmers mediates the fascinating patterns of schooling as well as their escape and attack routines. We study the fluid mechanics of single and multiple swimmers through simulations that rely on wavelet adapted vortex methods. Stochastic optimization and reinforcement learning algorithms are used to identify optimal shapes and motions for single and synchronized patterns for multiple swimmers. I will discuss how the orchestration of body deformations and vortex dynamics can result in thrust and energy savings for these artificial swimmers and compare these findings with swimming patterns of natural organisms. Lessons learned can assist the design and operation of energy efficient swimming devices. Bio: Petros Koumoutsakos is Professor of Computational Science at ETH Zurich. He received his Diploma (1986) in Naval Architecture at the National Technical University of Athens and a Master’s (1987) at the University of Michigan, Ann Arbor. He received his Master’s (1988) in Aeronautics and his PhD (1992) in Aeronautics and Applied Mathematics from the California Institute of Technology. He is Fellow of the American Society of Mechanical Engineers, the American Physical Society and the Society of Industrial and Applied Mathematics. He is recipient of the ACM Gordon Bell prize in Supercomputing and the Advanced Investigator Award by the European Research Council (2013). He is presently a Fellow at the Radcliffe Institute of Advanced Study at Harvard University.