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.
Model reduction by separation of variables: A comparison between hierarchical model reduction and proper generalized decomposition / Perotto, S.; Carlino, M. G.; Ballarin, F.. - 134:(2020), pp. 61-77. [10.1007/978-3-030-39647-3_4]
Model reduction by separation of variables: A comparison between hierarchical model reduction and proper generalized decomposition
Perotto, S.
;Ballarin, F.
2020-01-01
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.File in questo prodotto:
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