GALCIT Colloquium
Guggenheim 133 (Lees-Kubota Lecture Hall)
Optimisation and Learning for Artificial Swimmers
Petros Koumoutsakos,
Professor,
Department of Mechanical and Process Engineering,
ETH Zurich,
We seek to understand the interplay of hydrodynamics and behavioural traits in single and multiple swimmers. To this effect we perform simulations using a hierarchy of swimmer models, ranging from simple dipoles to fully resolved incompressible viscous flows, of self propelled 3D fish-like bodies. The simulations are coupled with optimisation algorithms to investigate responses such as escape and predation patterns by single swimmers.The interplay of hydrodynamics and behavioural traits is investigated for collective swimmers using reinforcement learning algorithms. I will discuss our findings in relation to observations in natural swimmers and outline some lessons learned that may serve as inspiration for engineering devices.
For more information, please contact Subrahmanyam Duvvuri by phone at 626-395-4455 or by email at [email protected].
Event Series
GALCIT Colloquium Series