IRTG Modern Inverse Problems (MIP)
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SSD Seminar Series with Prof. Masayuki Yano

20. Dezember 2021 @ 16:00 - 17:00

Prof. Masayuki Yano – Towards Reliable and Automated Model Reduction of Parametrized Nonlinear PDEs: Error Estimation, Adaptivity, and Application to Aerodynamics

Institute for Aerospace Studies, University of Toronto, Canada


Many engineering tasks, such as design optimization and uncertainty quantification, require rapid and reliable simulation of complex fluid flows for many different configurations. In this talk, we consider projection-based model reduction of parametrized nonlinear partial differential equations (PDEs) to accelerate the solution of many-query problems by several orders of magnitude, with applications to aerodynamics. The key ingredients are as follows: an adaptive high-order discontinuous Galerkin (DG) method, which provides stable and efficient solution of convection-dominated flows; reduced basis (RB) spaces, which provide rapidly convergent approximations of the parametric manifolds; the dual-weighted residual (DWR) method, which provides effective error estimates for quantities of interest; the empirical quadrature procedure (EQP), which provides hyperreduction of nonlinear PDEs; and adaptive training algorithms, which simultaneously trains the DG spaces, RB spaces, and EQP to meet the user-specified output error tolerance in a fully automated manner. We demonstrate the framework for parametrized aerodynamics problems modeled by the compressible Euler and Reynolds-averaged Navier-Stokes (RANS) equations, with applications to flight parameter sweep, design optimization, and data assimilation. The reduced models accelerate the computation by several orders of magnitude and provide error estimates in predictive settings.


20. Dezember 2021
16:00 - 17:00


a link for the Zoom meeting room will be send in the newsletter one week before the seminar starts. If you need any organizational help please contact office@aices.rwth-aachen.de