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Analysis And Research On Construction Monitoring Technology Of Long-span Cable-stayed Bridge

Posted on:2020-03-13Degree:MasterType:Thesis
Country:ChinaCandidate:G F YangFull Text:PDF
GTID:2392330620958103Subject:Bridge and tunnel project
Abstract/Summary:PDF Full Text Request
With the continuous development of bridge construction technology and construction technology,long-span bridges have gradually become a reality.However,cable-stayed bridges mainly use cable to pull the main girder directly above the pylon.It is also the special structure of the bridge that makes the bridge greatly increase its span capacity.Therefore,cable-stayed bridges are gradually appearing in more and more long-span bridges.Cable-stayed bridge has beautiful appearance and strong practicability,which makes it the choice of bridges across rivers.Due to the complexity of the bridge structure,in order to make the actual construction state of the bridge close to the ideal state,the bridge must be strictly monitored and controlled in the construction process.In this paper,relying on the solid engineering of the Kekedala Bridge,taking the construction monitoring of the Kekedala Bridge as the research object,combining the design data,actual construction scheme and the local environment of the project and other factors,the finite element model of the Kekedala Bridge is established by using the finite element software.The displacement variation of the main girder under different working conditions,the stress of the main girder and the cable-stayed cable are analyzed by the model.Power.According to the finite element software,the stability of the traveling basket model is analyzed,and the deformation of the traveling basket is obtained by combining the preloading test of the field traveling basket and the theory of the traveling basket deformation.Finally,the vertical formwork elevation of each beam section of the main beam is determined.Then,the sensitivity of Kekedala Bridge under completed condition is studied and analyzed by using finite element software.The sensitivity of main girder deflection,main girder stress and cable tension is mainly analyzed.Based on the sensitivity analysis of the main beam deflection,BP neural network is used to predict the elevation of the main beam by MATLAB programming.Meanwhile,the grey theory GM?1,1?model is used to predict the elevation of the main beam.The accuracy of the two prediction methods is compared and analyzed,and the prediction method suitable for this project is determined.The specific contents of this paper are as follows?1?Through the finite element software,the theoretical data of displacement variation,stress of main girder and cable tension of bridge girder under different working conditions are obtained,and the theoretical data are compared with the field measured data.It can be seen that the error between theoretical and actual values of each index of beam section is within the scope of the code requirements,of which the maximum error of stress of main girder is 12.7%,and the maximum error of cable tension is 12.7%.The maximum error of cable force is 4.68%,and the maximum error of displacement variation is 65 mm.The error is identified and optimized according to the index of the built beam section with large error,and the structural parameters are adjusted and the error is reduced in the subsequent construction of the beam section.?2?The finite element software ANSYS is used to establish the model of the hanging basket,and the stability of the hanging basket under different working conditions is analyzed.The maximum stress of the hanging basket is?max=158.6 MPa.The maximum deformation of the traveling basket cross beam after concrete pouring is epsilon?max=25.62mm.The strength and stiffness of the traveling basket meet the requirements.The deformation of the traveling basket in construction is determined by checking the stability of the traveling basket,preloading test on site and theoretical deformation of the traveling basket.The vertical formwork elevation of each section of the main beam is finally determined according to the design data,the deformation of the traveling basket and the anticlining of the bridge.?3?The sensitivity analysis of the main girder deflection,the main girder stress and the cable-stayed force is carried out by using the finite element software to establish the model of Kokedala Bridge under the condition of completion.It is concluded that the main girder self-weight is the main influencing factor of the main girder deflection and the cable-stayed force,while the temperature is the main influencing factor of the main girder stress,and the environmental change,temperature and the stiffness of the main girder are the secondary factors of the main girder deflection.The initial tension of cable force and the stiffness of main girder are the secondary factors affecting the stress of main girder and the cable force of stay cable,respectively.?4?Among the minor factors affecting the deflection of the main girder,the coupling effect of several minor factors on the deflection of the main girder is studied.It is concluded that the coupling effect of temperature and environment has a greater impact on the deflection of the main girder.In this way,the sensitivity analysis makes a more prepared identification and prediction of the errors in the actual construction process.?5?Based on the sensitivity analysis of the main girder deflection,the elevation of the main girder is predicted by grey theory GM?1,1?model and BP neural network system.Finally,the two prediction methods are compared and analyzed,and the prediction method of BP neural network is determined to be suitable for the prediction of the Kokedala Bridge.The method and scheme of bridge construction monitoring adopted in this paper have been applied to the Kokedala Bridge in practice.It also verifies the practicability and feasibility of the method and scheme.It also plays a guiding role in the construction process of the Kokedala Bridge and provides technical reference for the construction monitoring of the subsequent bridges.
Keywords/Search Tags:bridge construction control, sensitivity analysis, grey theory, BP neural network
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