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作 者:江钰 康宽彬 崔现良 陈月平 陈华鹏 JIANG Yu;KANG Kuan-bin;CUI Xian-liang;CHEN Yue-ping;CHEN Hua-peng(School of Transportation Engineering,East China Jiaotong University,Nanchang,Jiangxi 330013,China;China Railway Construction Group Corporation Limited,Beijing 100040,China)
机构地区:[1]华东交通大学交通运输工程学院,江西南昌330013 [2]中铁建设集团有限公司,北京100040
出 处:《工程力学》2023年第S01期234-240,共7页Engineering Mechanics
基 金:国家重点研发计划项目(2021YFE0105600);国家自然科学基金面上项目(51978263);江西省科技合作专项重点项目(20212BDH80022);江西省重点研发计划项目(20223BBH80002)。
摘 要:随着在役钢筋混凝土结构的不断退化,业主们迫切关心如何利用有限资金在恰当时候对量大面广的结构进行管理与维护。基于gamma随机过程,该文提出了一种适用于锈蚀钢筋混凝土柱的维护策略优化方法。通过分析锈蚀引起的混凝土柱退化情况,该文建立了适用于不同锈蚀程度与受力状态的混凝土柱残余承载力计算模型。同时,考虑到结构退化过程的不确定性,采用gamma过程对锈蚀柱的失效概率进行了预测,并通过平衡失效风险与维修成本的方法,确定了结构的最佳维护时间。通过一个数值算例验证了该文提出方法的可靠性和有效性。结果显示:损伤程度与受力状态对锈蚀柱残余承载力有较大影响;此外,锈蚀柱的允许退化极限越小,结构的最佳维护时间越早,对应的期望相对成本越高。With the continuous degradation of in-service reinforced concrete(RC)structures,owners are urgently concerned about managing and maintaining a sea of RC members at the proper time with limited funds.Thusly,an optimized approach for the maintenance strategy of corrosion-damaged RC columns is presented upon the gamma process.By analyzing the performance deterioration of the corroded RC columns,proposed are the calculation models for estimating the residual bearing capacity under different damaged levels and various loading conditions.Meanwhile,the gamma process is adopted here to predict the failure probability of corroded columns by considering the uncertainty of structural deterioration.Moreover,the optimal maintenance time of the structure is determined by balancing the maintenance cost and the risk of structural failure.A numerical example is given to demonstrate the effectiveness of the models proposed.The results show that:the residual bearing capacity of RC columns can be significantly affected by the rebar corrosion level and load condition;when the allowable degradation limit of the corroded structure is smaller,the optimal maintenance time of the structure is advanced,and the corresponding expected relative cost increases.
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