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Neural Network Application for Structure Design Optimization of Thin-Wall Structures

[+] Author Affiliations
Hesham Kamel

Military Technical College, Cairo, Egypt

Paper No. IMECE2011-63022, pp. 41-45; 5 pages
doi:10.1115/IMECE2011-63022
From:
  • ASME 2011 International Mechanical Engineering Congress and Exposition
  • Volume 9: Transportation Systems; Safety Engineering, Risk Analysis and Reliability Methods; Applied Stochastic Optimization, Uncertainty and Probability
  • Denver, Colorado, USA, November 11–17, 2011
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5495-2
  • Copyright © 2011 by ASME

abstract

Neural networks are trained to predict the response of a thin wall tube under dynamic impact loading then they are integrated with an optimization algorithm to improve the crashworthiness design of the thin wall tube. LS-DYNA is used to simulate the tube’s response under dynamic impact while MATLAB is used to train the neural networks and the optimization algorithm. The results show that the suggested approach succeeded in improving the thin wall tube design at an affordable computational cost. It is suggested that the approach can be expanded for the design improvement of more complex structures.

Copyright © 2011 by ASME

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