| In recent years,severe convective weather occurs frequently in mountainous and canyon areas,causing a large number of casualties and losses to personnel and property during the operation of Bridges in mountainous areas.In addition,because of the complex topography and wind environment in the mountainous areas,the design and construction of bridge in the mountainous areas must be based on a comprehensive master of the characteristics of canyon wind field.However,the study of wind field in the mountainous areas in our country started later,and the meteorological data at the bridge site is relatively lacking.Based on this,this thesis takes two long-span Bridges located in the western mountain gorge as the engineering background.According to the measured wind data of three-dimensional anemometer,the average wind and pulsating wind characteristics are studied.The non-stationary pulsating wind field of the bridge main beam is simulated by measured wind parameters,and the non-stationary buffeting response of the bridge is systematically analyzed and studied.The main research contents and conclusions of this thesis are as follows:(1)The measured data of two long-span Bridges were analyzed to obtain their average wind characteristics.Meanwhile,the EMD method and db system wavelet method were used to extract the time-varying average wind speed from the measured wind speed data,and the three components of the pulsating wind speed were separated to obtain the pulsating wind characteristics.The results show that the observed strong winds are mainly concentrated in spring and winter in the western mountainous area,with obvious seasonal variation characteristics,and the direction of incoming wind is consistent with that of the valley.The wind attack Angle is mainly negative in strong wind,which is quite different from the value specified in bridge design code.In addition,the energy of the three-component pulsating wind speed power spectrum is concentrated in the same frequency range,and the non-stationarity characteristics are obvious,and the mountain terrain is greatly affected.At the same time,the fluctuation range of the average turbulence intensity of the three components is roughly the same,and the ratio of transverse wind to downwind turbulence intensity has little difference with the specification,while the ratio of vertical wind to downwind turbulence intensity is much higher than the recommended range of the specification.(2)According to the field measured wind parameters,linear filtering method and harmonic synthesis method are used to simulate the non-stationary pulsating wind field of the bridge main beam.The correlation analysis,power spectrum test and EPSD estimation are carried out through the example,and the simulation results are compared and analyzed.The simulation accuracy of harmonic synthesis method is higher than that of linear filtering method.The simulated stable wind field was modulated into non-stable pulsating wind field,which provided necessary wind parameters for subsequent buffeting response analysis.(3)The ANSYS finite element model of two trans-canyon Bridges in the western mountainous region was established,and the buffeting response of the Bridges was analyzed using the classical multi-mode SRSS frequency domain method.The influences of different coherence functions,wind speed spectrum,wind attack Angle and turbulence intensity on the non-stationary buffeting displacement responses of the two Bridges were studied and compared.The analysis results show that the transverse buffeting displacement response of the two Bridges is the largest along the main beam,followed by the vertical one,and the torsion the least.In addition,the buffeting displacement response of the two Bridges is always the largest when the canonical coherence function and the canonical wind spectrum are selected.The different response dislocations of different Bridges do not show specific rules,but the mid-span displacement of the main span is greater than 1/4 section of the main span.And the greater the turbulence degree,the greater the influence on the buffeting displacement response. |