Details
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Applied and Computational Mechanics |
| Place of Publication | Cham |
| Pages | 229-247 |
| Number of pages | 19 |
| ISBN (electronic) | 978-3-030-38156-1 |
| Publication status | Published - 4 Mar 2020 |
Publication series
| Name | Lecture Notes in Applied and Computational Mechanics |
|---|---|
| Volume | 93 |
| ISSN (Print) | 1613-7736 |
| ISSN (electronic) | 1860-0816 |
Abstract
High fidelity structural problems that involve nonlinear material behaviour, when subjected to cyclic loading, usually demand infeasible computational resources; this demonstrates the need for efficient model order reduction (MOR) techniques in order to shrink these demands to fit into the available means. The solution of cyclic damage problems in a model order reduction framework is investigated in this chapter. A semi-incremental framework based on a large time increment (LATIN) approach is proposed to tackle cyclic damage computations under variable amplitude and frequency loadings. The involved MOR approach provides a low-rank approximation in terms of proper generalised decomposition (PGD) of the solution. The generated PGD basis can be interpreted as a set of linear subspaces altered on the fly to the current problem settings. The adaptation of PGD to new settings is based on a greedy algorithm that may lead to a large-sized reduced order basis (ROB). Thus, different orthonormalisation and compression techniques were evaluated to ensure the optimality of the generated ROB in [1] and will be overviewed here. The proposed implementation and a displacement formulated finite element (FE) incremental framework are compared to illustrate their differences in terms of memory footprint and computational time. Numerical examples with variable loadings are discussed, and a typical implementation is provided as open-source code, available at https://gitlab.com/shadialameddin/romfem.
ASJC Scopus subject areas
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computational Theory and Mathematics
Cite this
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Lecture Notes in Applied and Computational Mechanics. Cham, 2020. p. 229-247 (Lecture Notes in Applied and Computational Mechanics; Vol. 93).
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - A Semi-incremental Scheme for Cyclic Damage Computations
AU - Alameddin, Shadi
AU - Fau, Amélie
AU - Néron, David
AU - Ladevèze, Pierre
AU - Nackenhorst, Udo
N1 - Funding information: This research was funded by the German Research Foundation/Deutsche Forschungsgemeinschaft (DFG) through the International Research Training Group (IRTG) 1627.
PY - 2020/3/4
Y1 - 2020/3/4
N2 - High fidelity structural problems that involve nonlinear material behaviour, when subjected to cyclic loading, usually demand infeasible computational resources; this demonstrates the need for efficient model order reduction (MOR) techniques in order to shrink these demands to fit into the available means. The solution of cyclic damage problems in a model order reduction framework is investigated in this chapter. A semi-incremental framework based on a large time increment (LATIN) approach is proposed to tackle cyclic damage computations under variable amplitude and frequency loadings. The involved MOR approach provides a low-rank approximation in terms of proper generalised decomposition (PGD) of the solution. The generated PGD basis can be interpreted as a set of linear subspaces altered on the fly to the current problem settings. The adaptation of PGD to new settings is based on a greedy algorithm that may lead to a large-sized reduced order basis (ROB). Thus, different orthonormalisation and compression techniques were evaluated to ensure the optimality of the generated ROB in [1] and will be overviewed here. The proposed implementation and a displacement formulated finite element (FE) incremental framework are compared to illustrate their differences in terms of memory footprint and computational time. Numerical examples with variable loadings are discussed, and a typical implementation is provided as open-source code, available at https://gitlab.com/shadialameddin/romfem.
AB - High fidelity structural problems that involve nonlinear material behaviour, when subjected to cyclic loading, usually demand infeasible computational resources; this demonstrates the need for efficient model order reduction (MOR) techniques in order to shrink these demands to fit into the available means. The solution of cyclic damage problems in a model order reduction framework is investigated in this chapter. A semi-incremental framework based on a large time increment (LATIN) approach is proposed to tackle cyclic damage computations under variable amplitude and frequency loadings. The involved MOR approach provides a low-rank approximation in terms of proper generalised decomposition (PGD) of the solution. The generated PGD basis can be interpreted as a set of linear subspaces altered on the fly to the current problem settings. The adaptation of PGD to new settings is based on a greedy algorithm that may lead to a large-sized reduced order basis (ROB). Thus, different orthonormalisation and compression techniques were evaluated to ensure the optimality of the generated ROB in [1] and will be overviewed here. The proposed implementation and a displacement formulated finite element (FE) incremental framework are compared to illustrate their differences in terms of memory footprint and computational time. Numerical examples with variable loadings are discussed, and a typical implementation is provided as open-source code, available at https://gitlab.com/shadialameddin/romfem.
UR - http://www.scopus.com/inward/record.url?scp=85081558017&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-38156-1_12
DO - 10.1007/978-3-030-38156-1_12
M3 - Contribution to book/anthology
AN - SCOPUS:85081558017
SN - 978-3-030-38155-4
T3 - Lecture Notes in Applied and Computational Mechanics
SP - 229
EP - 247
BT - Lecture Notes in Applied and Computational Mechanics
CY - Cham
ER -