Prediction of static shear force and fatigue life of adhesive joints by artificial neural network
KOVOVE MATERIALY-METALLIC MATERIALS, vol.46, no.1, pp.51-57, 2008 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 46 Issue: 1
- Publication Date: 2008
- Journal Name: KOVOVE MATERIALY-METALLIC MATERIALS
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Page Numbers: pp.51-57
- Keywords: adhesive joints, fatigue, bonding strength, artificial neural network (ANN), BONDED CYLINDRICAL COMPONENTS, STRENGTH, MODEL
- Akdeniz University Affiliated: No
Abstract
In this study, a static shear force and fatigue life prediction model was developed using artificial neural network (ANN). The developed model was used to predict static shear force and fatigue life of adhesively bonded cylindrical joints for the surface roughness, bonding clearance and adherent such as steel, bronze and aluminium. The results showed that developed artificial neural network model was convenient and powerful tool for static shear force and fatigue life prediction of adhesively bonded cylindrical joints.