城市建筑对象对恶性攻击的脆弱性:基于异常暴力行为有限数据的评估

E. Vaidogas
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摘要

摘要:本文考虑了城市环境中所建(构)物对故意施加的异常作用(荷载)的脆弱性评估。正在分析的行动包括爆炸、车辆撞击和火灾,这些可能是由恐怖主义和破坏行为造成的,以及汽车因无意偏离道路而撞向建筑物等高度随机的事件。脆弱性通过称为脆弱性函数的数学模型进行评估,并为脆弱的建筑和运输结构、防护屏障和能源供应设施开发。易损性评估的结果是可以预见的破坏概率,并通过用于结构分析的数学模型进行建模。案例研究中,关于异常行为的信息可以以小型统计样本的形式表示,其中包含在攻击或意外事故的事后调查中获得的成分。其基本思想是应用统计(自举)重采样来估计损伤概率。重新采样程序应用于脆弱性函数的值,这些值可以为所讨论的异常行为造成的损害而开发。对异常动作值的小样本分量的脆弱性函数值进行估计。对易损性函数值进行重采样,得到由单侧置信区间极限表示的损伤概率的保守估计。对破坏概率的估计可用于对城市易损物的恢复水平进行决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fragility of Built Urban Objects to Vicious Attacks: Assessment by Means of Limited Data on Abnormal Violent Actions
Abstract An assessment of fragility of objects built (constructed) in urban environment to deliberately imposed abnormal actions (loads) is considered. The actions under analysis are explosions, vehicular impacts and fires that can be imposed by acts of terrorism and sabotage as well as such highly random events as car crashes into structures due to unintentional roadway departures. The fragility is assessed by means of mathematical models known as fragility functions and developed for vulnerable building and transportation structures, protective barriers, and energy supply facilities. The result of fragility assessment is the probability of the damage that can be foreseen and modelled by means of mathematical models used for structural analysis. The case is studied where information on an abnormal action can be expressed in the form of a small-size statistical sample with components acquired in post-mortem investigations of attacks or unintentional accidents. The basic idea is an application of the statistical (bootstrap) resampling for the estimation the damage probability. The resampling procedure is applied to values of the fragility function that can be developed for the damage caused by the abnormal action in question. The values of the fragility function are estimated for components of the small-size sample of abnormal action values. The resampling of the fragility function values yields a conservative estimate of the damage probability expressed by the limit of a one-sided confidence interval. The estimate of the damage probability can be applied to making decisions concerning the level of resilience of vulnerable urban objects.
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