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考虑行波效应的大跨度钢管混凝土拱桥易损性分析 被引量:1

Vulnerability Analysis of Long Span Concrete Filled Steel Tube Arch Bridges Considering Traveling Wave Effects
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摘要 为研究行波效应对大跨度钢管混凝土拱桥地震易损性的影响,采用有限元软件建立了桥梁的三维空间有限元模型,基于BP神经网络模型分析了大跨度钢管混凝土拱桥易损构件在行波效应与一致激励下的易损性。结果表明:采用BP神经网络模型建立的钢管混凝土拱桥地震响应平均预测误差为1.78%;考虑轻微损伤下,行波效应对拱上立柱易损性的影响较小,考虑中等损伤下,行波效应对拱上立柱易损性的有利影响先增大后减小,考虑严重损伤下,行波效应对拱上立柱易损性的有利影响随地面峰值加速度的增大越来越大。 To study the influence of traveling wave effect on the seismic vulnerability of large-span steel tube concrete arch bridges,a three-dimensional finite element model of the bridge was established using finite element software.Based on the BP neural network model,the vulnerability of vulnerable components of large-span steel tube concrete arch bridges under traveling wave effect and consistent excitation was analyzed.The results show that the average prediction error of seismic response of concrete filled steel tubular arch bridge established using BP neural network model is 1.78%;When considering slight damage,the traveling wave effect has a small impact on the vulnerability of columns on the arch.When considering moderate damage,the beneficial impact of traveling wave effect on the vulnerability of columns on the arch first increases and then decreases.When considering severe damage,the beneficial impact of traveling wave effect on the vulnerability of columns on the arch increases with the increase of peak surface acceleration.
作者 尹伟 YIN Wei(Hunan Maglev Group Co.,Ltd.,Changsha,Hunan 410006,China)
出处 《黑龙江交通科技》 2023年第6期63-65,69,共4页 Communications Science and Technology Heilongjiang
关键词 钢管混凝土拱桥 易损性分析 行波效应 一致激励 BP神经网络 concrete filled steel tube arch bridge vulnerability analysis traveling wave effect consistent motivation BP neural network
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