Application of Artificial Neural Network to Estimate the Fatigue Life of Shot Peened Ti-6Al-4V ELI Alloy

  1. T.S. Srivatsan and
  2. M. Ashraf Imam
  1. Saber Amin Yavari1,
  2. Navid Saeidi2 and
  3. Seied Hamidreza Maddah Hosseini1

Published Online: 10 NOV 2010

DOI: 10.1002/9781118013373.ch26

Fatigue of Materials: Advances and Emergences in Understanding

Fatigue of Materials: Advances and Emergences in Understanding

How to Cite

Yavari, S. A., Saeidi, N. and Hosseini, S. H. M. (2010) Application of Artificial Neural Network to Estimate the Fatigue Life of Shot Peened Ti-6Al-4V ELI Alloy, in Fatigue of Materials: Advances and Emergences in Understanding (eds T.S. Srivatsan and M. A. Imam), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118013373.ch26

Author Information

  1. 1

    Department of Materials Science and Engineering, Sharif University of Technology, Iran

  2. 2

    Department of Materials Engineering, Isfahan University of Technology, Iran

Publication History

  1. Published Online: 10 NOV 2010
  2. Published Print: 18 OCT 2010

ISBN Information

Print ISBN: 9780470943182

Online ISBN: 9781118013373

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Keywords:

  • artificial neural network;
  • Ti6Al4V ELI;
  • fatigue life

Summary

This chapter contains sections titled:

  • Introduction

  • Methods

  • Results and Discussions

  • Conclusions