Segmented real-time uncertainty-based updating of finite element model of cantilever casting arch bridge
TIAN Zhongchu
ZHANG Wei
CAI Yue
LIN Lexin
YANG Yike
Abstract:[Objective]During the construction process of cantilever casting concrete arch bridges,there are many uncertain factors such as material properties,construction techniques,and environmental conditions,which may lead to deviations between the initial finite element model and the actual structure.To make the finite element model accurately simulate the construction process,it is very important to update it.However,traditional model updating methods fail to fully consider the uncertainties present in the actual structure,which results in inconsistencies between the updated model and the actual situation.Therefore,based on the engineering projects of the Xixiu super bridge and the Qingshuijiang super bridge in Guizhou province,this paper studied the finite element model updating to address uncertainties in segmental construction.[Method]The response surface method was adopted to perform sensitivity analysis of the structural parameters during the construction process of cantilever casting arch bridges,so as to reduce the impact of non-sensitive parameters on the results of uncertainty model updating.Based on the identified sensitive parameters,a response surface surrogate model for a specific segment was obtained using the central composite design in Design Expert software.Interval analysis,which could quantify the uncertainty of parameters,and affine algorithm,capable of providing more precise solution intervals,was introduced to construct an affine-interval response surface function.This function was then optimized and solved for intervals by using the particle swarm optimization algorithm.The corrected parameter intervals were utilized in the model updating of the subsequent segment.[Results]Sensitivity analysis results show that the segmental volume weight of the arch ring,the cable force of the buckle,and the cable force of the anchor cable are sensitive parameters that significantly influence the response of the controlled structure during construction.Furthermore,in the uncertainty model updating for the 0# and 1# segments of the arch ring of the Xixiu super bridge,the study found that the corrected parameter intervals were significantly narrowed compared to the initial intervals.The structural responses of the updated model were found to be closer to the measured responses.Subsequently,a comparative analysis was conducted on the parameter intervals and structural responses of the Qingshuijiang super bridge and the Xixiu super bridge before and after the uncertainty model updating.The study found that the revised parameter intervals for the arch ring segments of both bridges significantly decreased compared to the initial intervals and were relatively close to the measured parameter intervals.In addition,the structural responses of the updated finite element model in the present and the later segments were more consistent with the measured values.This validates the applicability and effectiveness of the affine-interval response surface method in updating the uncertainty model of cantilever casting arch bridges.[Conclusion]The sensitivity parameters identified by the response surface method during the construction period of the cantilever casting arch bridges can effectively promote the updating of the uncertainty model.The affine-interval response surface method is indeed feasible in the uncertainty model updating for the segmental construction of cable-stayed cantilever casting arch bridges.The updated model can not only accurately reflect the structural response of the segment but also better predict the structural response of the next segment,thus it can be able to provide more accurate guidance for the subsequent construction stage and ensure the safety and controllability of the project.
Keywords:cantilever casting arch bridgearch ringfinite element model updatingresponse surface methodinterval analysisaffine algorithmparameter sensitivity analysissensitivity percentage
Publication Date:2025-05-25
Online Publishing Date:2025-08-15(First online date of this platform, not the publication date of the document)
Pages:11( 398-408 )
Journal of Shenyang University of Technology

Journal of Shenyang University of Technology

ISTICPKU
ISSN:1000-1646
Year, Vol.(Issue):2025,47(3)