...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Earthquake Engineering & Structural Dynamics >Development of empirical and analytical fragility functions using kernel smoothing methods
【24h】

Development of empirical and analytical fragility functions using kernel smoothing methods

机译：使用核平滑方法开发经验和分析脆弱性函数

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Fragility functions that define the probabilistic relationship between structural damage and ground motion intensity are an integral part of performance-based earthquake engineering or seismic risk analysis. This paper introduces three approaches based on kernel smoothing methods for developing analytical and empirical fragility functions. A kernel assigns a weight to each data that is inversely related to the distance between the data value and the input of the fragility function of interest. The kernel smoothing methods are, therefore, non-parametric forms of data interpolation. These methods enable the implicit treatment of uncertainty in either or both of ground motion intensity and structural damage without making any assumption about the shape of the resulting fragility functions. They are particularly beneficial for sparse, noisy, or non-homogeneous data sets. For illustration purposes, two types of data are considered. The first is a set of numerically simulated responses for a four-story steel moment-resisting frame, and the second is a set of field observations collected after the 2010 Haiti earthquake. The results demonstrate that these methods can develop continuous representations of fragility functions without specifying their functional forms and treat sparse data sets more efficiently than conventional data binning and parametric curve fitting methods. Moreover, various uncertainty analyses are conducted to address the issues of over-fitting, bias, and confidence intervals. Copyright (c) 2014 John Wiley & Sons, Ltd.
机译：定义结构破坏与地震动强度之间的概率关系的易碎性函数是基于性能的地震工程或地震风险分析的组成部分。本文介绍了三种基于核平滑方法的方法，用于开发解析和经验脆弱性函数。内核为每个数据分配一个权重，该权重与数据值与目标脆弱性函数的输入之间的距离成反比。因此，内核平滑方法是数据插值的非参数形式。这些方法可以隐式处理地面运动强度和结构破坏中的一者或两者的不确定性，而无需对所得脆性函数的形状进行任何假设。它们对于稀疏，嘈杂或不均匀的数据集特别有用。为了说明的目的，考虑两种类型的数据。第一个是对四层钢制抗弯框架的一组数值模拟响应，第二个是在2010年海地地震之后收集的一组野外观测资料。结果表明，与常规数据装箱和参数曲线拟合方法相比，这些方法可以开发出脆弱函数的连续表示而无需指定其功能形式，并且可以更有效地处理稀疏数据集。此外，进行了各种不确定性分析，以解决过度拟合，偏差和置信区间的问题。版权所有（c）2014 John Wiley＆Sons，Ltd.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号