Prediction of composite laminate residual strength based on a neural network approach
نویسندگان
چکیده
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.
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