Model reduction by separation of variables: A comparison between hierarchical model reduction and proper generalized decomposition

S. Perotto; M. G. Carlino; Francesco Ballarin

doi:10.1007/978-3-030-39647-3_4

Model reduction by separation of variables: A comparison between hierarchical model reduction and proper generalized decomposition

S. Perotto, M. G. Carlino, Francesco Ballarin^*

^*Autore corrispondente per questo lavoro

Polytechnic University of Milan

Risultato della ricerca: Contributo in libro › Contributo a conferenza

1 Citazioni (Scopus)

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.

Lingua originale	Inglese
Titolo della pubblicazione ospite	Lecture Notes in Computational Science and Engineering
Editore	Springer
Pagine	61-77
Numero di pagine	17
Volume	134
ISBN (stampa)	978-3-030-39646-6
DOI	https://doi.org/10.1007/978-3-030-39647-3_4
Stato di pubblicazione	Pubblicato - 2020

All Science Journal Classification (ASJC) codes

Modellazione e Simulazione
Ingegneria Generale
Matematica Discreta e Combinatoria
Controllo e Ottimizzazione
Matematica Computazionale

Keywords

hierarchical model reduction
proper generalized decomposition

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10.1007/978-3-030-39647-3_4

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UR - https://publicatt.unicatt.it/handle/10807/174183

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Model reduction by separation of variables: A comparison between hierarchical model reduction and proper generalized decomposition

Abstract

All Science Journal Classification (ASJC) codes

Keywords

Accesso al documento

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