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邓学晶,林倩,亓玉成,邹德高.平稳随机激励下耦合 Newmark滑移系统的可靠性分析[J].计算力学学报,2014,31(5):578~583
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平稳随机激励下耦合 Newmark滑移系统的可靠性分析
Dynamic reliability analysis of the coupled Newmark sliding system under stationary random excitation
投稿时间:2013-07-22  修订日期:2013-10-17
DOI:10.7511/jslx201405006
中文关键词:  动力可靠度  地震永久位移  滑动位移  随机振动
英文关键词:dynamic reliability  earthquake permanent displacement  sliding displacement  random vibration
基金项目:地震行业科研专项经费(201208013);国家自然科学基金(51138001,91215301);中央高校基本科研业务费专项资金资助项目.
作者单位E-mail
邓学晶 中国石油大学(华东) 工程力学系, 青岛 266555 dengxj@upc.edu.cn 
林倩 中国石油大学(华东) 工程力学系, 青岛 266555  
亓玉成 中国石油大学(华东) 工程力学系, 青岛 266555  
邹德高 大连理工大学 土木水利学院, 大连 116024  
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中文摘要:
      基于随机激励的离散形式,对耦合Newmark系统的动力可靠度问题进行解析分析。平稳随机激励下,耦合Newmark系统初始滑移极限状态方程可以写成n个标准正态随机变量的显式线性函数,并能给出可靠度指标的理论解。对于以相对滑移量为临界状态的情况,极限状态方程是n个标准正态随机变量的隐式函数,可借助静力可靠度方法进行求解。算例表明,系统初始滑移的设计点激励是以潜在滑动体自振频率为主频,振幅渐增的谐振时程;后者的失效概率与摩擦系数成非线性关系,存在合适的摩擦系数使失效概率最小。
英文摘要:
      Based on a discrete representation of the input random process,the dynamic reliability of a coupled Newmark sliding system under stationary excitation is investigated analytically.When the initial sliding of the system induced by stationary excitation is considered,the limit-state function can be expressed as an explicit linear function of n standard normal random variables,and the theoretical solution of reliability index can be obtained.If sliding more than a certain amount of relative displacement is considered as the failure criterion of the system,the limit-state function is expressed as an explicit nonlinear function of n standard normal random variables,and an approximate solution can be gained by using the static reliability methods.Examples show the design point excitation resulting in the initial relative sliding of the system is a harmonic wave with increasing amplitude,and its frequency is equal to the one of the system.There are nonlinear relations between probability values of failure for the system sliding more than a certain displacement and coefficients of friction of the system,and the optimal coefficient of friction which makes the minimum probability of failure can be found.
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