Dokumentdetails
ID

oai:arXiv.org:2407.18870

Thema
Computer Science - Computational E...
Autor
Sato, Yuki Terashima, Yuto Lewis Kondo, Ruho
Kategorie

Computer Science

Jahr

2024

Auflistungsdatum

31.07.2024

Schlüsselwörter
properties method computational homogenization
Metrisch

Zusammenfassung

Real-world physical systems, like composite materials and porous media, exhibit complex heterogeneities and multiscale nature, posing significant computational challenges.

Computational homogenization is useful for predicting macroscopic properties from the microscopic material constitution.

It involves defining a representative volume element (RVE), solving governing equations, and evaluating its properties such as conductivity and elasticity.

Despite its effectiveness, the approach can be computationally expensive.

This study proposes a tensor-train (TT)-based asymptotic homogenization method to address these challenges.

By deriving boundary value problems at the microscale and expressing them in the TT format, the proposed method estimates material properties efficiently.

We demonstrate its validity and effectiveness through numerical experiments applying the proposed method for homogenization of thermal conductivity and elasticity in two- and three-dimensional materials, offering a promising solution for handling the multiscale nature of heterogeneous systems.

;Comment: 25 pages, 7 figures

Sato, Yuki,Terashima, Yuto Lewis,Kondo, Ruho, 2024, Efficient computational homogenization via tensor train format

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