Full Content is available to subscribers

Subscribe/Learn More  >

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
  • 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


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



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In