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|Other Titles: ||The establishment of wind coefficient and spectrum estimation models for buildings using artificial neural networks|
|Authors: ||吳建緯;Wu, Jian-Wei|
|Keywords: ||類神經網路;輻狀基底函數;風工程;風力係數;風力頻譜;ANN;RBFNN;Wind Engineering;Wind Coefficient and Wind Force Spectrum|
|Issue Date: ||2013-04-13 11:49:14 (UTC+8)|
Wind resistant design of buildings oftenneeds to acquire wind coefficents and spectra from wind tunnel tests. Recently, the development of building design wind load standards of other countries has been gradually progresstoward database-assisted design methods. Using regression formulas to process and analyze experimental data of wind coefficients usually are not very accurate. Therefore, one of the most important issue is how to use experimental wind load aerodynamic database more effectively.
Wind tunnel test data of new building models, such asD/B 2.5, 1.5, 0.67, 0.4, and H/√A 3.5, 4.5, 5.5, 6.5, were added. In addition, the distribution of acrosswind and torsional windcoefficients were adopted to the new estimation model to increase accuracy.
The wind engineering research center of Tamkang University has successfully applied artificial neural networks (ANNs) to simulatewind force spectra. The other part of this research was to follow the previous approach using the new experimental data to train radial basis function neural networks (RBFNNs) to predict spectra. The RBFNN program was updated, the ANN architecture was fine tuned, and the allocating of training and verification data was investigated in order to achieve better accuracy of the model.
Finally, the ANN architecture was applied to the 2012 project, Applications of Aerodynamic Database on Building Design Wind Loads, from ABRI, Ministry of the Interior. All the ANNs were coded into the Window based wind load calculation software for wind coefficient and spectrum predictions and calculations. In conclusion, the result of the preliminary application is very well judging from the design cases investigated.
|Appears in Collections:||[土木工程學系暨研究所] 學位論文|
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