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Research On Hoisting Method Of Main And Secondary Arch Ribs And Arch Rib Linear Construction Control Of Space Y-shaped Steel Box Arch Bridge

Posted on:2024-09-15Degree:MasterType:Thesis
Country:ChinaCandidate:C WeiFull Text:PDF
GTID:2542307157979249Subject:Civil engineering
Abstract/Summary:PDF Full Text Request
Spatial Y-type steel box arch bridge is a special-shaped steel box arch bridge built for the first time in China.Due to the special characteristics of the combination of single and double arch ribs,the main and secondary arches of this bridge are under cooperative force,which makes the selection of the hoisting method of the main and secondary arch ribs of this bridge very important.At the same time,because the bridge is constructed by cable hoisting,the construction precision of arch rib is very high,so it is necessary to control arch rib linear construction.Therefore,this paper takes this bridge as the research background to study the hoisting method of main and secondary arch ribs and the prediction and control of arch rib alignment.The main work and research achievements of this paper are as follows:(1)Using finite element software,finite element modeling analysis is carried out on the two main and auxiliary arch rib lifting methods of spatial Y-type steel box arch bridge,and the section stress,deflection deformation and stability of arch rib at each construction stage are analyzed,and the two lifting methods are preliminally compared.(2)The AHM-TOPSIS comprehensive evaluation method was applied for the first time to the optimization of two lifting methods for the main and secondary arch ribs of spatial Y-type steel box arch bridge.Compared with the traditional analytic hierarchy process,it was simpler and clearer to ensure that the weight distribution of various indexes was more appropriate and the calculation process was more concise.This paper compares and selects two methods from five aspects: the sectional stress,deflection deformation and stability of arch rib,the construction cost and construction period of arch rib lifting.The optimal results show that the close degree of the construction method of the main and secondary arch rib lifting separately is higher than that of the construction method of the main and secondary arch rib lifting simultaneously,that is,the construction method of the main and secondary arch rib lifting separately is closer to the ideal scheme.Therefore,the hoisting method of main and secondary arch ribs separately is the best.(3)Aiming at the optimal hoisting method of main and auxiliary arch ribs,through the design of orthogonal test and the selection of orthogonal table,81 kinds of test conditions required by the original comprehensive test are converted into 9 kinds of orthogonal tests,which greatly improves the work efficiency and saves time.The test results show that the dead weight,elastic modulus and cable force are the three main sensitive construction parameters that affect the alignment of arch rib during construction,which are used as the input values of the linear control model.At the same time,through the single factor parameter sensitivity analysis of dead weight,elastic modulus and cable force,the influences of the above three parameters on the stress and deflection of arch rib in the process of lifting construction and the main control section are obtained.(4)The G-BP grey neural network is first applied to the arch rib linear construction control of spatial Y-type steel box arch bridge.By adjusting the parameters to establish the learning sample database to train the network,the error of the model meets the requirements.The trained network is used to predict the deflection of each control point of the arch rib of spatial Y-type steel box arch bridge.Compared with the measured deflection value of the existing lifting segments,the prediction result is better than that of BP neural network,which indicates that GBP grey neural network can predict and control the arch rib alignment of spatial Y-type steel box arch bridge.
Keywords/Search Tags:Space Y steel box arch bridge, AHM-TOPSIS, Orthogonal test, single factor test, G-BP grey neural network
PDF Full Text Request
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