Crushing behavior of laterally compressed composite elliptical tubes: Experiments and predictions using artificial neural networks
作者： El-Sadig Mahdi , Hany El Kadi , None
DOI: 10.1016/J.COMPSTRUCT.2007.05.009
关键词:
摘要: Abstract Composite materials have been increasingly used in the automobile industry for weight saving and part integration purposes. In this regard, composite elliptical tubes effectively employed as energy absorber devices. This increases need accurate simple prediction techniques to optimize these structures. The present work deals with implementation of artificial neural networks (ANN) technique crushing behavior absorption characteristics laterally loaded glass fiber/epoxy tubes. Predicted results are compared actual experimental data terms load carrying capacity capability showing good agreement. shows that ANN could be predict response collapsible devices subjected different loading conditions. As is case findings, predictions obtained using also show significant effect ellipticity ratio on
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