Paper Title:
Adaptive Neural Network Modelling in Fatigue life Prediction under Load History effects
  Abstract

Artificial intelligence (AI) techniques and in particular, adaptive neural networks (ANN) have been commonly used in order to Fatigue life prediction. The aim of this paper is to consider a new crack propagation principle based on simulating experimental tests on three point-bend (TPB) specimens, which allow predicting the fatigue life and fatigue crack growth rate (FCGR). An important part of this paper is estimation of FCG rate related to different load histories. The effects of different load histories on the crack growth life are obtained in different representative simulation and experiments.

  Info
Periodical
Advanced Materials Research (Volumes 284-286)
Chapter
Iron and Steel
Edited by
Xiaoming Sang, Pengcheng Wang, Liqun Ai, Yungang Li and Jinglong Bu
Pages
1266-1270
DOI
10.4028/www.scientific.net/AMR.284-286.1266
Citation
M. A. Razzaq, K. A. Ariffin, A. El Shafie, S. Abdullah, Z. Sajuri, N.A. Akeel, "Adaptive Neural Network Modelling in Fatigue life Prediction under Load History effects", Advanced Materials Research, Vols. 284-286, pp. 1266-1270, 2011
Online since
July 2011
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Price
$32.00
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