Journal
COMPUTERS & STRUCTURES
Volume 80, Issue 22, Pages 1699-1713Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0045-7949(02)00162-1
Keywords
artificial neural networks; composite materials; parameter identification; superconducting cable; elasto-plasticity
Ask authors/readers for more resources
This paper presents an example of the use of an artificial neural network (ANN) for parameter identification of a theoretical model of the behaviour of a fibrous composite under transversal cyclic loading. A set of parameters of a generalised elasto-plastic model is identified to ensure the best accordance between two families of graphs of stress: that predicted by the theory and the experimental one. The adaptation of the theoretical model to obtain a better description of the experimental data is described in the paper. The application of the ANN technique for parameter identification is presented. An interpretation of the nature of mechanical processes that govern the analysed experiment is proposed and confirmed by the analysis of identified parameters. (C) 2002 Elsevier Science Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available