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akaturk Akademik ölçüm

Makale detayı · 2010

Prediction of Bearing Strength of Two Serial Pinned Bolted Composite Joints using Artificial Neural Networks

Journal of Composite Materials

YÖKSİS OpenAlex ISSN 0021-9983 DOI 10.1177/0021998309353344 Atıf 9 SJR Q1 JCR Q2

10.1177/0021998309353344

YÖKSİS YÖKSİS makale kaydı

OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)

Özet

OpenAlex kaydı

İngilizce (OpenAlex)

The aim of this study is to investigate the improvement of an artificial neural network (ANN) method for the prediction of bearing strength of two serial pinned/bolted E-glass reinforced epoxy composite joints. The experimental data from the previous study with different geometrical parameters without torque and various applied torque were used for developing the ANN model. Comparisons of ANN results with desired values showed that there is a good agreement between input and output variables of the experimental data. Therefore, ANN was illustrated to be a valid powerful tool for the prediction of bearing strength of two serial pinned/bolted composite joints.

OpenAlex zenginleştirmesi

Konular

  • Mechanical Behavior of Composites
  • Advanced Fiber Optic Sensors
  • Mechanical stress and fatigue analysis

Tür: article Mechanical Behavior of Composites

İndeks bilgisi

WoS (JCR) ve Scopus (SJR) çeyrekleri ISSN ve yayın yılına göre. · 2010

Scopus (SJR) / WoS (JCR)

Journal of Composite Materials

Scopus (SJR) Q1 0,667 2010 yılı
WoS (JCR) Q2 JIF 1 2010 yılı

Üniversiteler

  • AKSARAY ÜNİVERSİTESİ

Yazarlar

  1. FARUK ŞEN
  2. MEHMET AYDIN KÖMÜR AKSARAY ÜNİVERSİTESİ
  3. ONUR SAYMAN