Prediction of static shear force and fatigue life of adhesive joints by artificial neural network

Sekercioglu T., Kovan V.

KOVOVE MATERIALY-METALLIC MATERIALS, cilt.46, sa.1, ss.51-57, 2008 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 46 Sayı: 1
  • Basım Tarihi: 2008
  • Dergi Adı: KOVOVE MATERIALY-METALLIC MATERIALS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.51-57
  • Anahtar Kelimeler: adhesive joints, fatigue, bonding strength, artificial neural network (ANN), BONDED CYLINDRICAL COMPONENTS, STRENGTH, MODEL
  • Akdeniz Üniversitesi Adresli: Hayır

Özet

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.