Artificial neural network application to the friction-stir welding of aluminum plates


Okuyucu H., Kurt A., ARCAKLIOĞLU E.

MATERIALS & DESIGN, cilt.28, ss.78-84, 2007 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 28 Konu: 1
  • Basım Tarihi: 2007
  • Doi Numarası: 10.1016/j.matdes.2005.06.003
  • Dergi Adı: MATERIALS & DESIGN
  • Sayfa Sayıları: ss.78-84

Özet

An artificial neural network (ANN) model was developed for the analysis and simulation of the correlation between the friction stir welding (FSW) parameters of aluminium (Al) plates and mechanical properties. The input parameters of the model consist of weld speed and tool rotation speed (TRS). The outputs of the ANN model include property parameters namely: tensile strength, yield strength, elongation, hardness of weld metal and hardness of heat effected zone (HAZ). Good performance of the ANN model was achieved. The model can be used to calculate mechanical properties of welded Al plates as functions of weld speed and TRS. The combined influence of weld speed and TRS on the mechanical properties of welded Al plates was simulated. A comparison was made between measured and calculated data. The calculated results were in good agreement with measured data. (c) 2005 Elsevier Ltd. All rights reserved.