Polymers and Polymer Composites

PREDICTION AND DETECTION OF FAILURES IN LAMINATED COMPOSITE MATERIALS USING NEURAL NETWORKS – A REVIEW

April 1, 2006 By: Addin A O; Sapuan S M; Mahdi E; Othman M Research article

Title: PREDICTION AND DETECTION OF FAILURES IN LAMINATED COMPOSITE MATERIALS USING NEURAL NETWORKS – A REVIEW
Page Range: p.433-441
Author(s): Addin A O; Sapuan S M; Mahdi E; Othman M
File size: 105K
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Journal: Polymers and Polymer Composites
Issue Year: ppc
Volume: 14
Issue No: No. 4

Abstract
This article describes combined computational techniques with the use of neural networks as a quantitative method, and natural frequencies, electrical conductivity, and lamb waves as non-destructive methods used to identify failures in laminated composite materials. Neural networks demonstrated robust and uncontroversial capabilities for complex failure detection and prediction in laminated composite materials with small errors. These failures include delamination, matrix cracking, fibre fracture and debonding. The presence of these failures is reported in terms of size, location and shape. 51 refs.


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