Artificial neural network application to the friction-stir welding of aluminum plates
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Date
2007
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier Sci Ltd
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
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.
Description
ARCAKLIOGLU, Erol/0000-0001-8073-5207
Keywords
friction stir welding, mechanical properties, ANN, modeling
Journal or Series
Materials & Design
WoS Q Value
Q2
Scopus Q Value
Q1
Volume
28
Issue
1
Citation
closedAccess
