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  • 标题:Prediction and Parametric Optimization on Mechanical Properties of Friction Stir Welding Joints of AA 6061 and AA 2014 Using Genetic Algorithm
  • 本地全文:下载
  • 作者:P.Hema ; N.Raviteja ; K.Ravindranath
  • 期刊名称:International Journal of Innovative Research in Science, Engineering and Technology
  • 印刷版ISSN:2347-6710
  • 电子版ISSN:2319-8753
  • 出版年度:2016
  • 卷号:5
  • 期号:3
  • 页码:3870
  • DOI:10.15680/IJIRSET.2016.0503093
  • 出版社:S&S Publications
  • 摘要:Friction Stir Welding is a solid state welding technique which heats metal to the temperature below recrystallization.FSW avoids welding defects like porosity and hot cracking which are common in conventional weldingtechniques due to alloy’s low re-crystallization temperature and higher heat dissipating nature. It was invented in 1991by the welding institute. This process combining (the metal is not melted) deformation heating and mechanical work toobtain high defect free joints. In the present study, dissimilar joints of AA6061 and AA2014 aluminum alloys weresuccessfully made by friction stir welding technique. The microstructure and mechanical behaviour of the welded jointswere investigated at different welding parameters. A mathematical model was developed to demonstrate a relationshipbetween the friction stir welding parameters and the mechanical properties of the dissimilar joints. The microstructuresof various regions were observed and analyzed by means of optical microscopy. The design of experiment has beendone with RSM with 15 numbers of experiments and prediction is done through ANOVA. Using ANOVA, thesignificance of welding parameters on mechanical properties of welded dissimilar joints is determined. And also byusing GENETIC ALGORITHM the optimal process parameters of welded joints are determined.
  • 关键词:Anova; Axial Force (AF); Genetic Algorithm; Tool Rotation Speed (TRS); Welding Speed (WS).
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