[Seminar] Some Ideas for Future Algorithms for Multidisciplinary Analysis and Optimization: Nonlinear Stability, Algorithm Optimization, and Monolithic Methods

In this presentation, three topics that have the potential to contribute to next-generation algorithms for single- and multi-disciplinary analysis and optimization will be covered. These include 1) entropy stable methods applicable to simplices and hence unstructured grids, 2) the use of numerical optimization in the design of algorithms, and 3) monolithic methods for multi-physics and optimization.

David Zingg is in his 35th year as a professor at the University of Toronto Institute for Aerospace Studies, where he was the Director from 2006-2016, and is currently the University of Toronto Distinguished Professor of Computational Aerodynamics and Sustainable Aviation. His research areas include aerodynamics, computational fluid dynamics, in particular high-order methods with the summation-by-parts property, and aerodynamic shape optimization. His current research is concentrated on applying aerodynamic shape optimization to the design of unconventional low-drag aircraft configurations motivated by the need to reduce greenhouse gas emissions from aircraft. Together with Harvard Lomax and Thomas Pulliam from the NASA Ames Research Center, Professor Zingg is a co-author of two well-known textbooks in computational fluid dynamics. He was awarded a prestigious Guggenheim Fellowship in 2004 and is a Fellow of the Canadian Academy of Engineering. Finally, he has supervised 44 PhD and 60 MASc students, many of whom hold senior positions in industry and academia.

(All are welcome to attend.)