Sparse approximations for contact mechanics

Fuente: arXiv
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Autori principali: Kollepara, Kiran Sagar, Aguado, José V., Guennec, Yves Le, Silva, Luisa, Borzacchiello, Domenico
Natura: Preprint
Pubblicazione: 2024
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author Kollepara, Kiran Sagar
Aguado, José V.
Guennec, Yves Le
Silva, Luisa
Borzacchiello, Domenico
author_facet Kollepara, Kiran Sagar
Aguado, José V.
Guennec, Yves Le
Silva, Luisa
Borzacchiello, Domenico
contents Low-rank model order reduction strategies for contact mechanics show limited dimensionality reduction due to linear inseparability of contact pressure field. Therefore, a dictionary based strategy is explored for creating efficient models for frictionless non-adhesive contact. A large dictionary of contact pressure trajectories is generated using a high-fidelity finite element model, while approximating the online query with a small number of dictionary entries. This is achieved by inducing sparsity in the approximation. Accuracy, computational effort and limitations of such methods are demonstrated on few numerical examples.
format Preprint
id arxiv_https___arxiv_org_abs_2406_11461
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Sparse approximations for contact mechanics
Kollepara, Kiran Sagar
Aguado, José V.
Guennec, Yves Le
Silva, Luisa
Borzacchiello, Domenico
Numerical Analysis
Low-rank model order reduction strategies for contact mechanics show limited dimensionality reduction due to linear inseparability of contact pressure field. Therefore, a dictionary based strategy is explored for creating efficient models for frictionless non-adhesive contact. A large dictionary of contact pressure trajectories is generated using a high-fidelity finite element model, while approximating the online query with a small number of dictionary entries. This is achieved by inducing sparsity in the approximation. Accuracy, computational effort and limitations of such methods are demonstrated on few numerical examples.
title Sparse approximations for contact mechanics
topic Numerical Analysis
url https://arxiv.org/abs/2406.11461