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YouTube

Localized Model Order Reduction for Parameter Optimization with Multiscale PDE Constraints

Hausdorff Center for Mathematics via YouTube

Overview

Explore localized model order reduction techniques for parameter optimization with multiscale PDE constraints in this 56-minute lecture by Mario Ohlberger from the Hausdorff Center for Mathematics. Delve into the reduced basis method for parameterized partial differential equations, examining its advantages in enabling high-fidelity real-time simulations and reducing computational costs in many-query applications. Investigate the challenges of large-scale and multiscale systems, focusing on localized training and on-the-fly enrichment strategies for PDE constrained optimization. Learn about the reduced basis - trust region framework, rigorous certification, and convergence concepts. Examine numerical experiments demonstrating the efficiency of proposed approaches in overcoming limitations of classical offline/online splitting methods.

Syllabus

Mario Ohlberger: Localized model order reduction for parameter optimization

Taught by

Hausdorff Center for Mathematics

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