Thursday, April 26, Volen 101, 2:00 p.m.
Numerical solvers cannot track unmodelled effects like noise, and this becomes a particularly serious issue in complex nonlinear systems like fluid flows. One way to address this problem is to use observations of the system being modelled---e.g., velocity field data from a fluid flow---to periodically correct the simulation. Changing the state variables of a running solver, however, can set off all sorts of unfriendly dynamics, so this {\sl data assimilation} process is not trivial. Moreover, gathering and processing data can be costly, both computationally and financially, so one should apply corrections only when and where they are needed---e.g., where the flow gradients are high. In this talk, I will discuss some of these issues in the context of a point-vortex model of an instrumented laboratory fluid flow: a planar air jet.
Speaker bio: Elizabeth Bradley did her undergraduate and graduate work at MIT, interrupted by a one-year leave of absence to row in the 1988 Olympic Games, and has been with the Department of Computer Science at the University of Colorado at Boulder since January of 1993. Her research interests include nonlinear dynamics, artificial intelligence, and control theory. She is the recipient of a NSF National Young Investigator award, a Packard Fellowship, a Radcliffe Fellowship, and the 1999 student-voted University of Colorado College of Engineering teaching award.
Host: Jordan Pollack