Prediction of Flutter Derivatives Using Artificial Neural Networks
學年 94
學期 2
發表日期 2006-07-16
作品名稱 Prediction of Flutter Derivatives Using Artificial Neural Networks
作品名稱（其他語言）
著者 Chen, C. H.; Lin, Y. Y.; Chen, J. H.
作品所屬單位 淡江大學土木工程學系
出版者 Yokohama: Japan Association for Wind Engineering
會議名稱 The Fourth International Symposium on Computational Wind Engineering
會議地點 Yokohama, Japan
摘要 This paper develops an artificial neural network (ANN) algorithm to predict the flutter derivatives of rectangular section models. Firstly, the ANN model uses the experimental dynamic responses of the section model in smooth flow to train a back-propagation (BP) neural network frame. The flutter derivatives can be determined using weight matrices in the neural network. The second part of this study is to predict the flutter derivatives of the rectangular section models without wind tunnel tests. Based on the given flutter derivatives of the rectangular section models tested in wind tunnel, the prediction frames of neural network are then established. The flutter derivatives of the rectangular section models, with the B/D ratios other than those obtained from the wind tunnel tests can be predicted by using this approach. The results show that this prediction scheme is reasonably well. By using this ANN approach, the database of the aerodynamic coefficients of bridge sections could be expanded.
關鍵字 artificial neural network;flat plate;flutter derivative;wind tunnel test
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間 20060716~20060719
通訊作者
國別 JPN
公開徵稿 Y
出版型式 紙本
出處 The Fourth International Symposium on Computational Wind Engineering, 4p.
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