The buffeting performance of kilometer-level high-speed railway suspension bridges has a great impact on the smooth operation of high-speed trains.To investigate the buffeting performance of the structure significantl...The buffeting performance of kilometer-level high-speed railway suspension bridges has a great impact on the smooth operation of high-speed trains.To investigate the buffeting performance of the structure significantly different from traditional suspension bridges,the first long-span high-speed railway suspension bridge,Wufengshan Yangtze River Bridge(WYRB),is taken as a numerical example to demonstrate the effects of structural parameters and wind field parameters on the buffeting responses.Based on the design information,the spatial finite element model(FEM)of WYRB is established before testing its accuracy.The fluctuating wind fields are simulated via both classical and stochastic wave based spectral representation method(SRM).Finite element method is further taken to analyze the parametric sensitivity on wind induced buffeting responses in time domain.The results show that the vertical displacement is more sensitive to the changing dead load than the lateral and torsional ones.The larger stiffness of the main girder and the lower sag-to-span ratio are both helpful to reduce the buffeting responses.Wind spectrum and coherence function are key influencing factors to the responses so setting proper wind field parameters are essential in the wind-resistant design stage.The analytical results can provide references for wind resistance analysis and selection of structural and fluctuating wind field parameters for similar long-span high-speed railway suspension bridges.展开更多
Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to th...Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to the analysis with support vector machine method, the drawback of determining the parameters only by experts' experience should be improved. After a detailed description of the methodology of SVM and simulated annealing, an improved algorithm was proposed for the automatic optimization of parameters using SVM method. An example has proved that the proposed method can efficiently select the parameters of the SVM method. And by optimizing the parameters, the forecasting accuracy of the max wind velocity increases by 34.45%, which indicates that the new SASVM model improves the forecasting accuracy.展开更多
基金Projects(51908125,51978155) supported by the National Natural Science Foundation of ChinaProject(W03070080)supported by the National Ten Thousand Talent Program for Young Top-notch Talents,China+1 种基金Project(BK20190359)supported by the Natural Science Foundation of Jiangsu Province,ChinaProject(BE2018120) supported by the Key Research and Development Plan of Jiangsu Province,China。
文摘The buffeting performance of kilometer-level high-speed railway suspension bridges has a great impact on the smooth operation of high-speed trains.To investigate the buffeting performance of the structure significantly different from traditional suspension bridges,the first long-span high-speed railway suspension bridge,Wufengshan Yangtze River Bridge(WYRB),is taken as a numerical example to demonstrate the effects of structural parameters and wind field parameters on the buffeting responses.Based on the design information,the spatial finite element model(FEM)of WYRB is established before testing its accuracy.The fluctuating wind fields are simulated via both classical and stochastic wave based spectral representation method(SRM).Finite element method is further taken to analyze the parametric sensitivity on wind induced buffeting responses in time domain.The results show that the vertical displacement is more sensitive to the changing dead load than the lateral and torsional ones.The larger stiffness of the main girder and the lower sag-to-span ratio are both helpful to reduce the buffeting responses.Wind spectrum and coherence function are key influencing factors to the responses so setting proper wind field parameters are essential in the wind-resistant design stage.The analytical results can provide references for wind resistance analysis and selection of structural and fluctuating wind field parameters for similar long-span high-speed railway suspension bridges.
基金Project(71071052) supported by the National Natural Science Foundation of ChinaProject(JB2011097) supported by the Fundamental Research Funds for the Central Universities of China
文摘Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to the analysis with support vector machine method, the drawback of determining the parameters only by experts' experience should be improved. After a detailed description of the methodology of SVM and simulated annealing, an improved algorithm was proposed for the automatic optimization of parameters using SVM method. An example has proved that the proposed method can efficiently select the parameters of the SVM method. And by optimizing the parameters, the forecasting accuracy of the max wind velocity increases by 34.45%, which indicates that the new SASVM model improves the forecasting accuracy.
