Predicting impact strength of perforated targets using artificial neural networks trained on FEM-generated datasets

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...

Full description

Bibliographic Details
Main Authors: Nikita Kazarinov, Aleksandr Khvorov
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-02-01
Series:Defence Technology
Subjects:
Machine learning
Impact
Dynamic fracture
FEM
Mesh distortion
Optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S2214914723001642

Internet

http://www.sciencedirect.com/science/article/pii/S2214914723001642

Similar Items