Using high-fidelity immersed simulations and data-driven surrogate models for forward and inverse problems in fluid-structure interaction by Prof. Wim van Rees

Exploiting fluid-structure interactions using flexible structures and actuation can improve performance in biologically inspired swimming and morphing airfoils. Open challenges in this realm are the efficient high-fidelity simulation of such fluid-structure interaction phenomena, especially in three-dimensions, as well as solving inverse problems for optimal design and control. Compounding the latter challenge in robotic design is the high-dimensional structure-actuation parameter space facilitated by modern developments in smart materials and structures, which prohibits brute-force optimization or control approaches. In this talk I will discuss some of our recent work on both forward and inverse problems in morphing structures and fluid-structure interaction, combining theoretical, numerical, and data-driven machine learning approaches. Specifically, I will first discuss the hydrodynamic benefits of curvature actuation in fluid-structure interaction. Second, I will discuss our methodologies and strategy for inverse-design, based on learning the shape-loading operator using data-driven surrogate models. Lastly, I will highlight our progress towards raising the ceiling of 3D simulations of fluid flows with moving/deforming boundaries, using high-order immersed methods and grid adaptation techniques.

Wim M. van Rees is Associate Professor in the department of Mechanical Engineering at Massachusetts Institute of Technology. He is affiliated with the Center for Ocean Engineering. He received his BSc and MSc from Delft University of Technology in Marine Techology, and his PhD from ETH Zurich in 2014. In 2015 he performed research as a postdoctoral fellow in the School of Engineering and Applied Sciences at Harvard University, and joined the MIT faculty in 2017. At MIT, he received Early Career awards from the Department of Energy in 2020, and from the Army Research Office in 2021. Wim's main research interests are to apply advanced numerical simulations to solve bio-inspired forward and inverse problems in fluids, solids, and fluid-structure interaction.