Reduced-order Modeling of Complex Fluid Flows

Tuesday, April 22, 2014 - 1:30pm - 2:30pm
Lind 305
Zhu Wang (University of Minnesota, Twin Cities)
In many scientific and engineering applications of complex
flows, computational efficiency is of paramount importance. Thus, model
reduction techniques are frequently used. To achieve a balance between the
low computational cost required by a reduced-order model and the complexity
of the target turbulent flows, appropriate closure modeling strategies need
to be employed. In this talk, we present reduced-order modeling strategies
synthesizing ideas originating from proper orthogonal decomposition and
large eddy simulation, develop rigorous error estimates and design
efficient algorithms for the new reduced-order models.