Brahe lecture on Multiscale Modeling
Date & Venue
December 14, 2017 at 15:15, ITC Campus, building 2, floor 4, room 2446.
Followed by a reception in building 4, floor 3, room 4308.
Speaker: Björn Engquist, Univ. of Texas at Austin
Björn Engquist received his PhD in numerical analysis from Uppsala University in 1975. He has been professor of mathematics at UCLA, and the Michael Henry Stater University Professor of Mathematics and Applied and Computational Mathematics at Princeton University. He was director of the Research Institute for Industrial Applications of Scientific Computing and of the Centre for Parallel Computers at the Royal Institute of Technology, Stockholm. At Princeton University, he was director of the Program in Applied and Computational Mathematics and the Princeton
Institute for Computational Science.
Engquist is a member of the Royal Swedish Academy of Sciences, the Royal Swedish Academy of Engineering Sciences and the Norwegian Academy of Science and Letters. He was a Guggenheim Fellow, received the first Society for Industrial and Applied Mathematics Prize in Scientific Computing and the Henrici Prize.
Engquist came to The University of Texas at Austin in 2004, where he holds the Computational and Applied Mathematics Chair I, and is director of the ICES Center for Numerical Analysis. Engquist’s research focuses on development and analysis of numerical methods for differential equations.
His earlier work includes the development of absorbing boundary conditions, homogenization theory and nonlinear high-resolution schemes for fluid dynamics. He is presently working on computational multi-scale methods and fast algorithms for wave propagation with applications in seismology.
The lecture will be introductory in approach and requires only some familiarity with basic numerical methods.
In multiscale processes different phenomena interact on different scales in time and space. Computer simulations of such processes are challenging since the smallest scales must be accurately represented over domains that cover the largest scales. This results in a very large number of unknowns and prohibitingly long computing times. We will briefly discuss analytical techniques and then focus on numerical multiscale methods, which have been developed to overcome this difficulty. We will illustrate these technologies by the examples of turbulent flow and the coupling between molecular and continuum models. We will also discuss some connections between multiscale modeling, information theory and data compression.