摘要
为了研究并揭示近断层地震下大跨钢管混凝土拱桥的损伤模式,以某三跨飞燕式钢管混凝土拱桥为研究背景,建立了考虑自平衡荷载、桩-土作用等效应的三维分析模型,依据近断层地震脉冲波的分类方法选取了9组近断层强震记录进行非线性时程分析,并基于关键构件的首次损伤时间,利用关键构件截面的PMM屈服面、PM曲线和截面应力评估方法,研究了桥例的地震损伤模式。结果表明:近断层地震的速度脉冲也是引起结构发生破坏的重要原因之一;钢筋混凝土边拱及钢管混凝土主拱均以面内弯曲损伤为主,K形风撑的斜撑是抗震薄弱部位,存在受压和受拉两种损伤模式;大跨钢管混凝土拱桥最易受损的部位是边拱拱脚,其次是边拱四分之一跨径处截面和K形风撑的斜撑,然后是主拱拱脚和主拱截面突变处,系杆和吊杆一般不会出现损伤状况,且有一定的强度储备。
In order to investigate and reveal the damage pattern of large-span CFST arch bridge subject to near-fault motions,a three-dimensional analysis model considering self-balancing load,pile-soil interaction and other effects is established with a three-span flying birds CFST arch bridge as the research background.Nine groups of near-fault strong earthquake records were selected based on the classification method of near-fault seismic pulse motions for nonlinear time-history analysis.Deploying PMM yield surfaces,PM curves and section stress evaluation method of critical components section,the seismic damage modes of bridge case are studied based on the definition of the first damage time of critical components.The results indicate that the velocity pulses of near-fault earthquakes are one of the important causes of structural damage.Both the reinforced concrete side arch and the CFST main arch are mainly in-plane bending damage,and the K-shaped diagonal braces are weak seismic sections which are characterized by compression and tension damage modes.The most vulnerable part of large-span CFST arch bridge is the side arch foot,followed by the cross section at quarter span of side arch and the K-shaped wind brace,then the main arch foot and the main arch section are suddenly changed.Tie bars and suspenders generally don’t suffer from damage and have a certain strength reserve.
作者
张令
徐略勤
ZHANG Ling;XU Lueqin(School of Civil Engineering,Chongqing Jiaotong University,Chongqing 400074,China;State Key Laboratory of Mountain Bridge and Tunnel Engineering,Chongqing Jiaotong University,Chongqing 400074,China)
出处
《地震工程与工程振动》
CSCD
北大核心
2020年第3期204-215,共12页
Earthquake Engineering and Engineering Dynamics
基金
重庆市教委科学技术研究项目(KJQN201900737)
重庆市自然科学基金项目(cstc2019jcyj-msxmX0691)。