A numerical study for prediction of forming load and experimental verification of bimetallic disc upsetting Numerička analiza za predviđanje nastalog opterećenja i eksperimentalna provjera sabijanja bimetalnog diska

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AYER Ö.

Tehnicki Vjesnik, cilt.24, sa.6, ss.1679-1688, 2017 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 24 Sayı: 6
  • Basım Tarihi: 2017
  • Doi Numarası: 10.17559/tv-20160130154750
  • Dergi Adı: Tehnicki Vjesnik
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1679-1688
  • Anahtar Kelimeler: Artificial neural network (ANN), Bimetallic materials, DEFORM-3D, Finite element method (FEM), Load analysis, Upper bound method (UB), Upsetting
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Trakya Üniversitesi Adresli: Evet

Özet

Forming of disc samples composed from aluminium and copper in performed study was examined with upsetting procedure. An approach for prediction deformation load of upsetting processes is developed. This study combines the finite element method model, neural network model and upper bound method to simulate and predict the deformation load in upsetting of bimetallic materials. The Finite Element Method (FEM) results were obtained from DEFORM-3D software and they were compared and validated with experiments by taking forming load into consideration. Also, Artificial Neural Network (ANN) model was used to analyze and predict the forming load for different process parameters. The Upper Bound (UB) model was also proposed to estimate the forming load and the results were compared with experiments. It was understood that calculated results were in concordance with experimental results in upsetting of bimetallic hollow discs. Thus, proposed ANN, FEM and UB models provide a valuable insight into the parameters affecting forming load and can be named as useful tools to predict the forming load without the need of any experiments.