WIT Press

Prediction Of Composite Laminate Residual Strength Based On A Neural Network Approach

Price

Free (open access)

Paper DOI

10.2495/AI940071

Volume

6

Pages

8

Published

1994

Size

781 kb

Author(s)

R. Teti & G. Caprino

Abstract

In this paper, the problem of tensile strength prediction of composite laminates containing artificially implanted holes is confronted. An approach based on the integration of acoustic emission and load data through neural network is presented. The obtained results show that neural networks can be a useful tool in the monitoring of fracture behavior of composite laminates through acoustic emission detection and analysis. 1. Introduction The identification of defects and the assessment of defect criticality through nondestructive evaluation (NDE) is a very attractive research topic in the field of composite materials. One of the main obstacles to the further development and diffusion of composite material applications is the lack or scarcity of NDE methods being inexpe

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