Transactions of Materials Processing (소성∙가공)

The Korean Society for Technology of Plasticity and materials processing (한국소성∙가공학회)
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Numerical Prediction of Temperature-Dependent Flow Stress on Fiber Metal Laminate using Artificial Neural Network

인공신경망을 사용한 섬유금속적층판의 온도에 따른 유동응력에 대한 수치해석적 예측

  • Received : 2018.04.13
  • Accepted : 2018.07.18
  • Published : 2018.08.01
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Abstract

The flow stresses have been identified prior to a numerical simulation for predicting a deformation of materials using the experimental or analytical analysis. Recently, the flow stress models considering the temperature effect have been developed to reduce the number of experiments. Artificial neural network can provide a simple procedure for solving a problem from the analytical models. The objective of this paper is the prediction of flow stress on the fiber metal laminate using the artificial neural network. First, the training data were obtained by conducting the uniaxial tensile tests at the various temperature conditions. After, the artificial neural network has been trained by Levenberg-Marquardt method. The numerical results of the trained model were compared with the analytical models predicted at the previous study. It is noted that the artificial neural network can predict flow stress effectively as compared with the previously-proposed analytical models.

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References

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