期刊
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
卷 45, 期 12, 页码 1955-1976出版社
WILEY
DOI: 10.1002/eqe.2734
关键词
structural capacity; seismic demand; ground motion selection; nonlinear dynamic analysis; fragility; multiple intensity measures; uncertainty and correlation
资金
- Foundation of Science and Technology (FCT) of Portugal [PTDC/ECM-EST/3062/2012]
- Fundação para a Ciência e a Tecnologia [PTDC/ECM-EST/3062/2012] Funding Source: FCT
State-of-the-art methods for the assessment of building fragility consider the structural capacity and seismic demand variability in the estimation of the probability of exceeding different damage states. However, questions remain regarding the appropriate treatment of such sources of uncertainty from a statistical significance perspective. In this study, material, geometrical and mechanical properties of a number of building classes are simulated by means of a Monte Carlo sampling process in which the statistical distribution of the aforementioned parameters is taken into consideration. Record selection is performed in accordance with hazard-consistent distributions of a comprehensive set of intensity measures, and issues related with sufficiency, efficiency, predictability and scaling robustness are addressed. Based on the appraised minimum number of ground motion records required to achieve statistically meaningful estimates of response variability conditioned on different levels of seismic intensity, the concept of conditional fragility functions is presented. These functions translate the probability of exceeding a set of damage states as a function of a secondary sufficient intensity measure, when records are selected and scaled for a particular level of primary seismic intensity parameter. It is demonstrated that this process allows a hazard-consistent and statistically meaningful representation of uncertainty and correlation in the estimation of intensity-dependent damage exceedance probabilities. Copyright (c) 2016 John Wiley & Sons, Ltd.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据