Reduced‐order FFT‐based homogenisation by tensor approximation
Abstract: We enhanced the efficiency of Fast Fourier transform (FFT) based Galerkin methods on numerical homogenisation problems by exploiting low‐rank tensor approximations in canonical, Tucker, and tensor train formats. This leads to a significant reduction in computational complexity and memory requirement. The advantages of the approach are demonstrated in a numerical example of a model homogenisation problem with stochastic heterogeneous material coefficients.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Reduced‐order FFT‐based homogenisation by tensor approximation ; volume:19 ; number:1 ; year:2019 ; extent:2
Proceedings in applied mathematics and mechanics ; 19, Heft 1 (2019) (gesamt 2)
- Urheber
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Liu, Dishi
Vondřejc, Jaroslav
Ladecký, Martin
Matthies, Hermann
- DOI
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10.1002/pamm.201900386
- URN
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urn:nbn:de:101:1-2022072207375401576764
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:29 MESZ
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Beteiligte
- Liu, Dishi
- Vondřejc, Jaroslav
- Ladecký, Martin
- Matthies, Hermann
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