Adaptive and Parallel Multiscale Framework for Modeling Cohesive Failure in Engineering Scale Systems
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911937708687360 |
|---|---|
| author | Kim, Sion Kissel, Ezra Matous, Karel |
| author_facet | Kim, Sion Kissel, Ezra Matous, Karel |
| contents | The high computational demands of multiscale modeling necessitate advanced parallel and adaptive strategies. To address this challenge, we introduce an adaptive method that utilizes two microscale models based on an offline database for multiscale modeling of curved interfaces (e.g., adhesive layers). This database employs nonlinear classifiers, developed using Support Vector Machines from microscale sampling data, as a preprocessing step for multiscale simulations. Next, we develop a new parallel network library that enables seamless model selection with customized communication layers, ensuring scalability in parallel computing environments. The correctness and effectiveness of the hierarchically parallel solver are verified on a crack propagation problem within the curved adhesive layer. Finally, we predict the ultimate bending moment and adhesive layer failure of a wind turbine blade and validate the solver on a difficult large-scale engineering problem. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_00006 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Adaptive and Parallel Multiscale Framework for Modeling Cohesive Failure in Engineering Scale Systems Kim, Sion Kissel, Ezra Matous, Karel Distributed, Parallel, and Cluster Computing Computational Engineering, Finance, and Science Numerical Analysis The high computational demands of multiscale modeling necessitate advanced parallel and adaptive strategies. To address this challenge, we introduce an adaptive method that utilizes two microscale models based on an offline database for multiscale modeling of curved interfaces (e.g., adhesive layers). This database employs nonlinear classifiers, developed using Support Vector Machines from microscale sampling data, as a preprocessing step for multiscale simulations. Next, we develop a new parallel network library that enables seamless model selection with customized communication layers, ensuring scalability in parallel computing environments. The correctness and effectiveness of the hierarchically parallel solver are verified on a crack propagation problem within the curved adhesive layer. Finally, we predict the ultimate bending moment and adhesive layer failure of a wind turbine blade and validate the solver on a difficult large-scale engineering problem. |
| title | Adaptive and Parallel Multiscale Framework for Modeling Cohesive Failure in Engineering Scale Systems |
| topic | Distributed, Parallel, and Cluster Computing Computational Engineering, Finance, and Science Numerical Analysis |
| url | https://arxiv.org/abs/2407.00006 |