Prediction of Abrasive Wear Rate of in Situ Cu–Al2O3 Nanocomposite using Artificial Neural Networks

Faculty Engineering Year: 2012
Type of Publication: ZU Hosted Pages: 953-963
Authors:
Ahmed Abou ElWafa Megahed Abou ElWafa Elbasyouni
Journal: The International Journal of Advanced Manufacturing Technology SpringerLink publications Volume: 62
Keywords : Prediction , Abrasive Wear Rate , , Situ Cu–Al2O3    
Abstract:
In this work, artificial neural networks (ANNs) technique was used in the prediction of abrasive wear rate of Cu–Al2O3 nanocomposite materials. The abrasive wear rates obtained from series of wear tests were used in the formation of the da
    
     
 
       

Author Related Publications

  • Ahmed Abou ElWafa Megahed Abou ElWafa Elbasyouni, "On the Prediction of Surface Roughness in Turning Operation using Artificial Neural Networks", Cairo University, 2000 More
  • Ahmed Abou ElWafa Megahed Abou ElWafa Elbasyouni, "Experimental Evaluation of Delamination in Drilling of Fiber Reinforced Polymeric Composite Materials", كلية الهندسة - جامعة الزقازيق, 2009 More
  • Ahmed Abou ElWafa Megahed Abou ElWafa Elbasyouni, "Prediction of Delamination Size in Drilling FRP Composite Materials using Artificial Neural Networks", كلية الهندسة - جامعة الزقازيق, 2009 More
  • Ahmed Abou ElWafa Megahed Abou ElWafa Elbasyouni, "Ultrasonic Mixing of Nanoparticles in Epoxy Resin", Housing & Building National Research Center, 2010 More
  • Ahmed Abou ElWafa Megahed Abou ElWafa Elbasyouni, "Machinability Analysis in Drilling Woven GFR/Epoxy Composites: Part I- Effect of Machining Parameters", Elsevier Ltd., 2010 More

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