Model reduction by separation of variables: a comparison between Hierarchical Model reduction and Proper Generalized Decomposition

Keywords

Advanced Numerical Methods for Scientific Computing
Code:
62/2018
Title:
Model reduction by separation of variables: a comparison between Hierarchical Model reduction and Proper Generalized Decomposition
Date:
Thursday 13th December 2018
Author(s):
Perotto, S.; Carlino, M.G.; Ballarin, F.
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Abstract:
Hierarchical Model reduction and Proper Generalized Decomposition both exploit separation of variables to perform a model reduction. After setting the basics, we exemplify these techniques on some standard elliptic problems to highlight pros and cons of the two procedures, both from a methodological and a numerical viewpoint.