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

Year 2020, , 813 - 819, 01.09.2020

İhsan Toktaş , M. Tolga Özkan Fulya Erdemir , Nurullah Yuksel

https://doi.org/10.2339/politeknik.683270

Cited By: 4

Abstract

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.

Keywords

Stress Concentration Factor (SCF), , Crankshaft Design, Artificial Neural Network (ANN)

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

Abstract

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. 

Keywords

Stress concentration factor (SCF), crankshaft design, artificial neural network (ANN)

References

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