Font Size: a A A

Research On Construction Control Of Arch Layer-by-layer And Segment-by-segment Pouring Long Span Reinforced Concrete Box Arch Bridge

Posted on:2017-02-18Degree:MasterType:Thesis
Country:ChinaCandidate:B LiFull Text:PDF
GTID:2272330488998446Subject:Civil engineering
Abstract/Summary:PDF Full Text Request
With the continuous development of Chinese transportation construction and the gradual progress of the bridge construction technology, bridge construction control as an important part of the bridge construction technology, its importance is widely recognized by the bridge builders.At the western mountains and the canyon,Large span reinforced concrete arch bridge is the first bridge type. The error analysis theory and optimal control theory are used in the construction control process.In this paper, the construction control of large span box arch bridge is studied, which is based on the two main span 80m reinforced concrete box arch bridge in Qianqing highway in the west of Hunan.(1)The research status of the reinforced concrete arch bridge, the box arch bridge construction technology and construction control method are summarized.(2) The theory and method of construction control are summarized, and the optimal control theory of box arch bridge is obtained through the comparison of the construction control theory.(3) The theory and algorithm of BP neural network method are discussed in detail, which provides the theoretical basis for the construction control of the layer-by-layer and segment-by-segment.(4) Using BP neural network method, layer-by-layer and segment-by-segment pouring of Jiangkou Bridge and Pushituo Bridge are controlled, So that the final alignment of the bridge is good agreement with the design status.(5) The influence of the structure axis line and the internal force of the main arch by layer-by-layer and segment-by-segment pouring sequence is analyzed to provide reference for the determination of pouring sequence of the same kind of bridge construction.
Keywords/Search Tags:Layer-by-layer and segment-by-segment construction method, Different pouring sequence, BP neural network method, Parameter identification, State prediction
PDF Full Text Request
Related items