Predicting impact strength of perforated targets using artificial neural networks trained on FEM-generated datasets
The paper considers application of artificial neural networks (ANNs) for fast numerical evaluation of a residual impactor velocity for a family of perforated PMMA (Polymethylmethacrylate) targets. The ANN models were trained using sets of numerical results on impact of PMMA plates obtained via dynam...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2024-02-01
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| Series: | Defence Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214914723001642 |