Neural identification for critical flutter load of a polar-orthotropic annular plate

Authors:
I. Takahashi
Affiliations:
Department of Mechanical Engineering, Kanagawa Institute of Technology, Japan
Venue:
ICAAICSE '01 Proceedings of the sixth international conference on Application of artificial intelligence to civil & structural engineering
Year:
2001

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Abstract

With increasing size and complexity of machines and vessels, the inverse problems of continuous bodies are becoming important. In this paper the possibility of using a Multilayer Perceptron Network trained with the Backpropagation Algorithm for detecting the critical flutter load of tapered annular plates is studied. The considered model is a polar-orthotropic plate, using a transfer matrix method, to estimate the changes in various modal parameters, caused by the shape parameters and support conditions of plates.