Yaser Ismail
An ABAQUS® plug-in for generating virtual data required for inverse analysis of unidirectional composites using artificial neural networks
Ismail, Yaser; Wan, Lei; Chen, Jiayun; Ye, Jianqiao; Yang, Dongmin
Authors
Abstract
This paper presents a robust ABAQUS® plug-in called Virtual Data Generator (VDGen) for generating virtual data for identifying the uncertain material properties in unidirectional lamina through artificial neural networks (ANNs). The plug-in supports the 3D finite element models of unit cells with square and hexagonal fibre arrays, uses Latin-Hypercube sampling methods and robustly imposes periodic boundary conditions. Using the data generated from the plug-in, ANN is demonstrated to explicitly and accurately parameterise the relationship between fibre mechanical properties and fibre/matrix interphase parameters at microscale and the mechanical properties of a UD lamina at macroscale. The plug-in tool is applicable to general unidirectional lamina and enables easy establishment of high-fidelity micromechanical finite element models with identified material properties.
Citation
Ismail, Y., Wan, L., Chen, J., Ye, J., & Yang, D. (2022). An ABAQUS® plug-in for generating virtual data required for inverse analysis of unidirectional composites using artificial neural networks. Engineering with Computers, 38(5), 4323-4335. https://doi.org/10.1007/s00366-021-01525-1
| Journal Article Type | Article |
|---|---|
| Acceptance Date | Oct 14, 2021 |
| Online Publication Date | Oct 31, 2021 |
| Publication Date | Oct 1, 2022 |
| Deposit Date | Oct 15, 2024 |
| Publicly Available Date | Oct 22, 2024 |
| Journal | Engineering with Computers |
| Print ISSN | 0177-0667 |
| Publisher | Springer Verlag |
| Peer Reviewed | Peer Reviewed |
| Volume | 38 |
| Issue | 5 |
| Pages | 4323-4335 |
| DOI | https://doi.org/10.1007/s00366-021-01525-1 |
| Keywords | Plug-in; Unidirectional lamina; Artificial neural networks; Periodic boundary conditions; Finite element modelling |
| Public URL | https://hull-repository.worktribe.com/output/4866196 |
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© The Author(s) 2021.
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