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Titolo:
Fatigue life prediction of unidirectional glass fiber/epoxy composite laminae using neural networks
Autore:
Al-Assaf, Y; El Kadi, H;
Indirizzi:
Amer Univ Sharjah, Sharjah, U Arab Emirates Amer Univ Sharjah Sharjah U Arab Emirates jah, Sharjah, U Arab Emirates
Titolo Testata:
COMPOSITE STRUCTURES
fascicolo: 1, volume: 53, anno: 2001,
pagine: 65 - 71
SICI:
0263-8223(200107)53:1<65:FLPOUG>2.0.ZU;2-4
Fonte:
ISI
Lingua:
ENG
Keywords:
fatigue behavior; composite materials; artificial neural networks;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
17
Recensione:
Indirizzi per estratti:
Indirizzo: El Kadi, H Amer Univ Sharjah, POB 26666, Sharjah, U Arab Emirates Amer Univ Sharjah POB 26666 Sharjah U Arab Emirates Emirates
Citazione:
Y. Al-Assaf e H. El Kadi, "Fatigue life prediction of unidirectional glass fiber/epoxy composite laminae using neural networks", COMP STRUCT, 53(1), 2001, pp. 65-71

Abstract

Fatigue behavior of unidirectional glass fiber/epoxy composite laminae under tension-tension and tension-compression loading is predicted using artificial neural networks (ANN). Stress-life experimental data were obtained for fiber orientation angles of 0 degrees, 19 degrees, 45 degrees, 71 degreesand 90 degrees. These tests were performed under stress ratios of 0.5, 0 and -1. The feedforward network used, provided accurate modeling between theinput parameters (maximum stress, R-ratio, fiber orientation angle) and the number of cycles to failure. Although a small number of experimental datapoints were used for training the neural network, the results obtained arecomparable to other current fatigue life-prediction methods. (C) 2001 Elsevier Science Ltd. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 07/07/20 alle ore 12:44:55