Methodology for Development of Physics-Based Tsunami Fragilities
Methodology for Development of Physics-Based Tsunami Fragilities
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DOI：
10.1061/(asce)st.1943-541x.0001715
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发表时间：
2017-05-01
影响因子：
4.1
通讯作者：
Cox, Daniel T.
中科院分区：
文献类型：
--
作者：
Attary, Navid;van de Lindt, John W.;Cox, Daniel T.
海啸影响世界各地的沿海地区，造成人员伤亡和对社区的灾难性破坏。脆弱性函数构成了个体结构一级大多数风险和复原力分析的基础，从而使社区一级的有形基础设施组成部分得以纳入。对于海啸荷载，已经开发的绝大多数脆弱性是基于现场的震后观测，通常是特定于事件的现场。在本文中，提出了一种方法来生成基于物理海啸脆弱性函数，使用矢量强度的措施，如海啸流的深度和流速及其组合。所提出的方法依赖于蒙特卡洛模拟考虑材料的不确定性，并包括在海啸力计算的认识不确定性。本文研究了海啸脆弱性曲线中常用的不同海啸强度测度（水深、流速和动量通量）对结构响应的预测能力，提出了一种新的海啸强度测度（动量通量运动矩），它代表结构的倾覆力矩。该方法是使用一个应用程序的例子，包括钢框架结构和脆弱性功能的基础上的动量通量的运动学矩的说明，是一个更好的预测与较少的认知不确定性。(C)2016年美国土木工程师协会。
Tsunamis affect coastal regions around the world, resulting in fatalities and catastrophic damage to communities. Fragility functions form the basis of most risk and resilience analyses at the individual structure level, thereby allowing physical infrastructure components to be included at the community level. For tsunami loading, the vast majority of fragilities that have been developed are based on postevent observations in the field, which are usually specific to the site of the event. In this paper, a methodology to generate physics-based tsunami fragility functions is proposed, using vector intensity measures, such as tsunami flow depth and flow velocity and several combinations thereof. The proposed methodology relies on Monte Carlo Simulation for consideration of material uncertainties and includes epistemic uncertainties in the tsunami force calculation. The ability of different tsunami intensity measures (flow depth, flow velocity, and momentum flux), which are common in the literature, to predict the response of structures are investigated, and a new intensity measure (kinematic moment of momentum flux) that represents overturning moment of a structure for tsunami fragility curves is proposed. The methodology is illustrated using an application example consisting of a steel moment frame structure and fragility functions based on the kinematic moment of momentum flux are presented and shown to be a better predictor with less epistemic uncertainty. (C) 2016 American Society of Civil Engineers.