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ARTIFICIAL NEURAL NETWORKS FOR THE PREDICTION OF MECHANICAL-BEHAVIOR OF METAL-MATRIX COMPOSITES

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Field Value
 
Title ARTIFICIAL NEURAL NETWORKS FOR THE PREDICTION OF MECHANICAL-BEHAVIOR OF METAL-MATRIX COMPOSITES
 
Creator MUKHERJEE, A
SCHMAUDER, S
RUHLE, M
 
Description In this paper we demonstrate the power of artificial neural networks in predicting strengthening in the transverse direction of metal matrix composites by regularly arranged strong fibers. A neural network is trained in different ways based on a numerical study in which the fiber volume fraction and the matrix hardening ability was studied systematically for fibers in a hexagonal arrangement loaded at 0 and 30 degrees transverse direction and for a square arrangement of fibers loaded at 0 and 45 degrees transverse directions. Strengthening predictions are then made for hardening cases of both fiber arrangements which were not covered by the finite element calculations as well as for arbitrary loading directions not achievable by simple finite element unit cell calculations in the case of square fiber arrangements.
 
Publisher PERGAMON-ELSEVIER SCIENCE LTD
 
Date 2011-08-23T15:20:35Z
2011-12-26T12:56:29Z
2011-12-27T05:45:19Z
2011-08-23T15:20:35Z
2011-12-26T12:56:29Z
2011-12-27T05:45:19Z
1995
 
Type Article
 
Identifier ACTA METALLURGICA ET MATERIALIA, 43(11), 4083-4091
0956-7151
http://dx.doi.org/10.1016/0956-7151(95)00076-8
http://dspace.library.iitb.ac.in/xmlui/handle/10054/10557
http://hdl.handle.net/10054/10557
 
Language en