Probabilistic Capacity Models and Fragility Estimates for Reinforced Concrete Columns based on Experimental Observations
Probabilistic Capacity Models and Fragility Estimates for Reinforced Concrete Columns based on Experimental Observations
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DOI：
10.1061/(asce)0733-9399(2002)128:10(1024
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发表时间：
2002-10
期刊：
影响因子：
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通讯作者：
P. Gardoni;A. Kiureghian;K. Mosalam
中科院分区：
文献类型：
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作者：
P. Gardoni;A. Kiureghian;K. Mosalam
开发了一种构建结构构件概率承载能力模型的方法。基于观测数据，使用贝叶斯更新来评估未知的模型参数。该方法妥善考虑了偶然不确定性和认知不确定性。基于大量现有的实验观测结果，该方法用于构建承受循环荷载的圆形钢筋混凝土柱的变形和抗剪承载能力的单变量和双变量概率模型。概率承载能力模型用于估计结构构件的易损性。制定了易损性的点估计和区间估计，它们隐含或明确地反映了认知不确定性的影响。例如，估计了一个典型桥梁柱在最大变形和剪力需求方面的易损性。
A methodology to construct probabilistic capacity models of structural components is developed. Bayesian updating is used to assess the unknown model parameters based on observational data. The approach properly accounts for both aleatory and epistemic uncertainties. The methodology is used to construct univariate and bivariate probabilistic models for deformation and shear capacities of circular reinforced concrete columns subjected to cyclic loads based on a large body of existing experimental observations. The probabilistic capacity models are used to estimate the fragility of structural components. Point and interval estimates of the fragility are formulated that implicitly or explicitly reflect the influence of epistemic uncertainties. As an example, the fragilities of a typical bridge column in terms of maximum deformation and shear demands are estimated.