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David Williams Colloquium
October 19, 2018 @ 2:00 PM – 3:00 PM
On Friday, October 19th at 2:00 pm in the 4th Floor Active Learning classroom at 3401 Walnut Street, Wing A, Professor David Williams of Penn State will give a talk titled:
“The Stabilization of Finite Element Methods for Compressible Flows”
Abstract:
There are many unique challenges in designing robust and high-fidelity methods for solving the compressible Navier-Stokes equations. These challenges can be (at least partially) remedied by embracing methods that are constructed within a rigorous mathematical framework. This is one of the reasons why finite element methods with their strong mathematical foundation are attractive. However, there remain several open questions regarding their suitability for solving the compressible Navier-Stokes equations. In particular, there are questions about the possibility of constructing robust, and versatile stabilization for finite element methods over a wide range of Reynolds and Mach numbers. In this talk, the speaker (David M. Williams) will attempt to discuss the non-linear stability of finite element methods, and in particular `entropy stability’, `L2 stability’, and `kinetic energy stability’. In addition, he will discuss the practical benefits of each type of stability, and recent advances in the development of more stable methods.
Bio
David M. Williams is an assistant professor at The Pennsylvania State University in the Mechanical Engineering Department. He came to Penn State from the Flight Sciences division of Boeing Commercial Airplanes and Boeing Research and Technology, where he worked for several years as a computational fluid dynamics engineer. Williams received his M.S. and Ph. D. in Aeronautics and Astronautics at Stanford University. He holds a B.S.E. in Aerospace Engineering from the University of Michigan. He has made significant advances in the design of numerical algorithms for computational fluid dynamic simulations. Currently, his research focuses on employing high-order Finite Element schemes to more accurately predict unsteady flows.”