International Journal of Naval Architecture and Ocean Engineering

The Society of Naval Architects of Korea (대한조선학회)
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In-plane and out-of-plane bending moments and local stresses in mooring chain links using machine learning technique

  • Lee, Jae-bin (Department of Naval Architecture and Ocean Engineering, Inha University) ;
  • Tayyar, Gokhan Tansel (Department of Naval Architecture and Marine Engineering, Istanbul Technical University) ;
  • Choung, Joonmo (Department of Naval Architecture and Ocean Engineering, Inha University)
  • Received : 2021.02.22
  • Accepted : 2021.11.16
  • Published : 2021.11.30
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Abstract

This paper proposes an efficient approach based on a machine learning technique to predict the local stresses on mooring chain links. Three-link and multi-link finite element analyses were conducted for a target chain link of D107 with steel grade R4; 24,000 and 8000 analyses were performed, respectively. Two serial Artificial Neural Network (ANN) models based on a deep multi-layer perceptron technique were developed. The first ANN model corresponds to multi-link analyses, where the input neurons were the tension force and angle and the output neurons were the interlink angles. The second ANN model corresponds to the three-link analyses with the input neurons of the tension force, interlink angle, and the local stress positions, and the output neurons of the local stress. The predicted local stresses for the untrained cases were reliable compared to the numerical simulation results.

Keywords

Acknowledgement

This study was supported by Inha Research Grant.

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