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Cited 64 time in webofscience Cited 82 time in scopus
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Fail-are of carbon/epoxy composite tubes under combined axial and torsional loading 1. Experimental results and prediction of biaxial strength by the use of neural networks SCIE SCOPUS

Title
Fail-are of carbon/epoxy composite tubes under combined axial and torsional loading 1. Experimental results and prediction of biaxial strength by the use of neural networks
Authors
Lee, CSHwang, WPark, HCHan, KS
Date Issued
1999-01
Publisher
ELSEVIER SCI LTD
Abstract
Biaxial tests have been conducted on cross-ply carbon/epoxy composite tube under combined torsion and axial tension/compression up to failure. Strength properties and distributions were evaluated with reference to the biaxial loading ratio. The scatter of the biaxial strength data was analyzed by using a Weibull distribution function. Artificial neural networks were introduced to pre diet failure strength by means of the error back-propagation algorithm for learning, providing a different and new approach to the representation of complicated behavior of composite materials. further prediction is made from experimental data by the use of Tsai-Wu theory and a combined optimized tensor polynomial theory. Comparison shows that the artificial neural network has the smallest root-mean-square error of the three prediction methods. (C) 1999 Elsevier Science Ltd. All rights reserved.
Keywords
stress/strain curves; failure criterion; artificial neural networks (ANN); biaxial strength; fiber reinforced plastics (FRP); COMBINED EXTERNAL-PRESSURE; WINDING ANGLE; STRAIN; STRESS
URI
https://oasis.postech.ac.kr/handle/2014.oak/20278
DOI
10.1016/S0266-3538(99)00038-X
ISSN
0266-3538
Article Type
Article
Citation
COMPOSITES SCIENCE AND TECHNOLOGY, vol. 59, no. 12, page. 1779 - 1788, 1999-01
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박현철PARK, HYUN CHUL
엔지니어링 대학원
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