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Construction risk analysis of cantilever casting mid-span closure of bridge in reservoir area

Author(s):


Medium: journal article
Language(s): English
Published in: Journal of Physics: Conference Series, , n. 1, v. 2680
Page(s): 012020
DOI: 10.1088/1742-6596/2680/1/012020
Abstract:

In order to assess the impact of frequent microseismic and cyclic water flow forces on the bridge cantilever casting construction in the Three Gorges reservoir area, a limited element-quantum-orthogonal experimental design-neural network-Monte Carlo simulation method was used to analyze the risk assessment of the construction. The orthogonal experimental design method is utilized to generate probability distribution samples of water velocity, water height, and microseismic acceleration. These samples are then combined with a finite element model and trained using a BP neural network. This approach aims to establish a nonlinear mapping relationship between each control parameter and the axial deviation value in the mid-span closure, and then the Monte Carlo simulation is used to generate the random influence parameter, which can be substituted into the trained BP neural network to predict the risk of the error in the mid-axial deviation. The results suggested that the risk probability of the medial axis deviation of the closure section due to the coupling effect of water flow force and high-frequency microseismicity had reached 5.06%, and the risk of line deviation of the cantilever casting construction of the bridge in the reservoir area needed to be paid sufficient attention and prevented. The risk of line deviation of the cantilever casting construction of the reservoir bridge needs to attract enough attention and precaution.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1088/1742-6596/2680/1/012020.
  • About this
    data sheet
  • Reference-ID
    10777523
  • Published on:
    12/05/2024
  • Last updated on:
    12/05/2024
 
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