The Taub Faculty of Computer Science Events and Talks
Gilead Tadmor (Northeastern University, Boston)
Tuesday, 02.08.2011, 11:30
Model order reduction is essential for feasible analysis, design,
realtime control of distributed systems. Recent uses also include
accelerating detailed simulations and the extraction of actionable
meaning from large scale data streams. Alas, a mature and
mathematically rigorous theory is largely limited to the linear case,
and even there, the mere computational complexity its tools entail,
restrict its use to relatively moderate dimensions. Heuristics fill in
the gap, with successions of intuitive patches, with very mixed results.
Our motivation comes from active flow control (AFC), a field driven by needs of
truly epic proportions: From energy efficiency of air, ground and maritime
transportation, through clean and efficient combustion and wind energy,
micro-fluidic, diagnostic chips, artificial hearts and other bio-engineering
designs, to HVAC and bio-chem defense. Arguably, the lack of adequate
low order models is a major impediment for real progress and transition
to wide-range usage.
We present a rational approach to Galerkin-type model order reduction
that tracks and addresses longstanding impediments at their first-principles
roots - the Navier-Stokes equation. Embedding flow states in parameterized
inertial manifolds, is used as to address difficult practical and conceptual
problems, including unsteady boundaries (e.g., flapping wings), boundary
actuation and transient deformation of coherent structures.