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考虑材料性能退化的大跨径悬索桥主缆时变可靠度分析

Analysis of Time-varying Reliability of Main Cables in Long-span Suspension Bridges Considering Material Performance Degradation
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摘要 钢丝腐蚀是影响大跨径悬索桥主缆力学性能的主要因素之一。为研究大跨径悬索桥在考虑主缆钢丝腐蚀下的结构可靠度退化规律,提出了一种考虑材料性能退化的主缆时变可靠度评估方法。首先推导分析了钢丝受到的主要腐蚀类型与其腐蚀机理,建立了考虑钢丝腐蚀下的材料本构模型。其次根据可靠度理论建立了考虑主缆钢丝腐蚀的结构功能函数,并以年平均抗力损失率为指标衡量主梁的腐蚀水平。最后采用BP神经网络拟合了悬索桥结构响应面,结合Monte Carlo抽样模拟法设计了不同腐蚀程度下的主缆时变可靠度计算方法,以某大跨径悬索桥为工程背景,探讨了不同腐蚀程度与材料分项系数下的主缆时变可靠度退化规律。结果表明:BP神经网络可以精准拟合悬索桥随机变量与结构响应之间的映射关系,10个验证集样本的平均相对误差仅为1.47%;以年平均抗力损失率为标准,当钢丝腐蚀速率越快时,其服役期内的可靠度指标退化越快,且该速率随着服役年限的增加而增加;材料分项系数取值越大时,相同腐蚀水平下的主缆结构可靠度指标更高,当考虑主缆钢丝腐蚀引起的材料性能退化时,设计材料分项系数宜取偏大值。 Steel wire corrosion is one of the main factors affecting the mechanical properties of the main cables of long-span suspension bridges.A time-varying reliability evaluation method for main cables considering material performance degradation is proposed to study the structural reliability degradation law of long-span suspension bridges under the consideration of main cable steel wire corrosion.Firstly,the main types of corrosion on steel wires and their corrosion mechanisms were derived and analyzed,and a material constitutive model considering steel wire corrosion was established.Secondly,a structural function considering the corrosion of the main cable steel wire was established based on reliability theory,and the corrosion level of the main beam was measured using the annual average resistance loss rate as an indicator.Finally,a BP neural network was used to fit the response surface of the suspension bridge structure,and a Monte Carlo sampling simulation method was used to design a time-varying reliability calculation method for the main cable under different corrosion levels.Taking a large-span suspension bridge as the engineering background,the degradation law of the time-varying reliability of the main cable under different corrosion levels and material sub coefficients was explored.The results show that BP neural network can accurately fit the mapping relationship between random variables and structural response of suspension bridges,and the average relative error of 10 validation set samples is only 1.47%;based on the annual average resistance loss rate,the faster the corrosion rate of the steel wire,the faster its reliability index deteriorates during its service life,and this rate increases with the increase of service life;the larger the value of the material sub coefficient,the higher the reliability index of the main cable structure under the same corrosion level.When considering the material performance degradation caused by the corrosion of the main cable steel wire,it is advisable to take a larger value for the design material sub coefficient.
作者 施权君 吴欣 卓小丽 秦志 袁野真 SHI Quanjun;WU Xin;ZHUO Xiaoli;QIN Zhi;YUAN Yezhen(Guangxi Baining Expressway Co.,Ltd.,Nanning,Guangxi 530000,China;Hunan Communications Research Institute Co.,Ltd.,Changsha,Hunan 410114,China;Guangxi Transportation Science and Technology Group Co.,Ltd.,Nanning,Guangxi 530000,China)
出处 《公路工程》 2024年第3期6-12,105,共8页 Highway Engineering
基金 2021年度交通运输行业重点科技项目(2021-ZD7-098) 湖南省交通科技项目(202045) 湖南省交通科技项目(202206) 广西科技计划项目(桂科AD19245152)。
关键词 悬索桥 主缆可靠度 钢丝腐蚀 材料退化 BP神经网络 suspension bridge main cable reliability steel wire corrosion material degradation BP neural network
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