In this talk, I will review some of our ongoing activities around high-fidelity and low-dimensional data-driven modeling of multiphysics interfaces, with a particular emphasis on fluid-structure interaction. High-fidelity modeling implies the solutions of coupled partial differential equations from the first principle physical laws, whereas data-driven modeling includes a combination of projection-based subspace models and deep neural networks. Using in-house codes, our target applications range from small-scale energy harvesting and sensing devices to bio-inspired flyers/swimmers to large-scale industrial modeling of marine vehicles and propellers.
This lecture will be delivered in person in LSK 306 and also streamed via Zoom. If you do not receive IAM seminar announcements by email, please RSVP here to receive the Zoom link.