Crushing analysis of energy absorbing materials using artificial neural networks. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Rogala, M; Gajewski, J; Głuchowski, D
• Is Part Of: Journal of physics. Volume 1736:Issue 1(2021)
• Publication Date: 2021-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1736/1/012026
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: This article presents the use of artificial neural networks in data analysis. The subject of the research were energy-absorbing materials under oblique loading. The forces obtained during the analysis were used to determine the crushing indicators. The numerical analysis was performed using the FEM Abaqus software. The specimens were loaded with the same force at different angles, i.e. 15, 30, 45, 60 degrees. During the numerical analyses, the normal and shear forces were measured. The tests were carried out under both static and dynamic load. On the basis of the MLP and RBF networks, analyses were carried out to study the relationship between the foam properties and the crushing efficiency indicators.