Determination of Stress Concentration Factor (Kt) for a Crankshaft under Bending Loading: An Artificial Neural Networks Approach

Toktaş İ., Özkan M. T., Erdemir F., Yuksel N.

JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, cilt.23, sa.3, ss.813-819, 2020 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 23 Sayı: 3
  • Basım Tarihi: 2020
  • Dergi Adı: JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.813-819
  • Anahtar Kelimeler: Stress Concentration Factor (SCF), crankshaft design, Artificial Neural Network (ANN), SECTIONS
  • Gazi Üniversitesi Adresli: Evet

Özet

Crankshafts are used in especially engines. Crankshafts are usually effected bending and torsional stress. These loading situations are important for design of engine and its parts. Crankshaft design requires design experience and engineering calculations. When the engineering calculation is performed, stress concentration factor is put into effect. These factors are usually obtained from Stress concentration factor Charts. Reading the real stress concentration factor from charts can be resulted in getting from false values. This study is an update work of old studies. Using the new computer techniques stress concentration factor values were converted into numerical values. Stress concentration factor values were collected in a database. Artificial Neural Network (ANN) Model was improved using the database. ANN model is gave to us time economy and high accuracy of obtaining the stress concentration values.