Abstract Fragility curves are used in earthquake engineering for assessing the seismic vulnerability of structures or systems. Direct estimations of fragility curves by means of simulation-based approaches lead generally to relevant computational costs, especially when the failure region is characterized by small probabilities of occurrence. Simplified hypotheses are therefore introduced in the common practice to approximate the dependency between the structural response and the associated seismic intensity level. The study proposes a non-parametric methodology to estimate analytical fragility curves without specific assumptions on their final shape. The approach starts by identifying all the subsets characterized by the same values of the chosen seismic intensity measure parameter. Then, the failure region is mapped by means of a classification algorithm coupled with a polynomial kernel. Finally, the conditional failure probability is computed by associating the samples generated in each subset to the corresponding classification score. A stochastic earthquake model is employed to define the seismic dataset and the uncertainty associated with the ground motion records. Two case studies are analyzed in which the non-parametric methodology is compared against three popular parametric approaches and a reference solution. The proposed approach shows an overall higher accuracy and efficiency, especially in case of rare failure domains.

中文翻译：

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一种计算分析非参数脆性曲线的有效方法

摘要 脆性曲线在地震工程中用于评估结构或系统的地震脆弱性。通过基于模拟的方法直接估计脆性曲线通常会导致相关的计算成本，特别是当故障区域的特征是发生概率很小时。因此，在通常的实践中引入了简化的假设，以近似估计结构响应与相关地震烈度水平之间的相关性。该研究提出了一种非参数方法来估计分析脆性曲线，而无需对其最终形状进行特定假设。该方法首先识别由所选地震强度测量参数的相同值表征的所有子集。然后，故障区域通过与多项式核耦合的分类算法进行映射。最后，通过将每个子集中生成的样本与相应的分类分数相关联来计算条件故障概率。随机地震模型用于定义地震数据集和与地震动记录相关的不确定性。分析了两个案例研究，其中将非参数方法与三种流行的参数方法和参考解决方案进行了比较。所提出的方法显示出整体更高的准确性和效率，尤其是在罕见故障域的情况下。随机地震模型用于定义地震数据集和与地震动记录相关的不确定性。分析了两个案例研究，其中将非参数方法与三种流行的参数方法和参考解决方案进行了比较。所提出的方法显示出整体更高的准确性和效率，尤其是在罕见故障域的情况下。随机地震模型用于定义地震数据集和与地震动记录相关的不确定性。分析了两个案例研究，其中将非参数方法与三种流行的参数方法和参考解决方案进行了比较。所提出的方法显示出整体更高的准确性和效率，尤其是在罕见故障域的情况下。