SGER: A multivariate calibration of St-Id for applications to constructed facilities

摘要：在过去的十年中，结构识别(ST-ID)作为结构健康监测(SHM)、基于性能的工程(PBE)和资产管理(AM)的核心和使能概念越来越受到重视。美国国会、联邦政府机构和美国建筑工程师学会现在承认的三个范例对改善基础设施性能至关重要。ST-ID的目标是通过数学模型和实验响应数据的关联来推断结构系统的不可测量属性(例如，边界条件和连续性条件、材料刚度、损伤等)。基本的假设是，结构的可测量响应(例如，位移、应变、加速度等)之间有足够的相关性。以及所需的不可测量属性，从而可以可靠地推断它们。尽管被广泛接受，我们目前对这一关键假设的验证几乎完全是由轶事证据提供的，既不全面，也不能量化(例如，振型比频率对损伤更敏感)。这一知识鸿沟严重依赖于用户的直觉和启发式，并排除了与ST-ID应用相关的总不确定性(随机和偏差)的可靠估计。为了解决这一知识鸿沟，拟议的研究被塑造为一种多变量校准，其中将通过使用基于概率的可识别性指数ID(类似于可靠性指数)来检验和量化各种ST-ID方法可靠地推断期望不可测量属性的变化的能力。此次校准将在德雷克塞尔智能基础设施研究所(DI3)的实验室物理模型上进行，该研究所的设计和建造类似于普通的板梁桥。为了实现此校准所需的控制，该模型能够模拟几种常见的边界条件、损坏场景和结构复杂性的来源(例如局部非线性)，并能够配置多个级别的冗余和不规则性(例如倾斜)。虽然这项研究的主要基本目标是确定？可辨识性？对于基于物理的响应指数(例如，模态参数)和基于非物理的模型(例如，神经网络)，还将满足确定模型更新过程推断不可测量属性的绝对值的能力的次要基本目标。智力价值：本研究的智力价值在于其目的在于定量地建立响应指数/已识别模型与所构建系统的不可测量属性之间的因果关系？一种关系，作为ST-ID进程的基础。虽然到目前为止，ST-ID应用程序提供了一些关于这种关系的见解，但这些见解既不全面，也不定量，这就排除了它们的普遍性。作者认为，这种知识差距是从已建设施中提取可靠和广泛适用的性能测量的根本障碍，这阻碍了SHM、PBE和AM的有意义的应用拟议的工作将是对已建系统严格调查这种关系的首次尝试，并代表着朝着更可靠和更科学的形式的ST-ID迈出的必要的第一步。广泛的影响：拟议的研究将使整个ST-ID社区参与第一次损害检测基准研究，明确表示已建设施的现实方面(例如结构复杂性)以及获取数据的现实方法(例如环境监测和履带卡车测试)。这项研究的结果将通过时事通讯、会议和期刊以及通过开发一个互动网站广泛传播。这项研究的综合教育部分将把DI3实验室的物理模型纳入德雷克塞尔大学和卡内基梅隆大学(DU和CMU)的本科结构分析课程。这项工作的目标将是展示所构建系统的结构行为的鲜为人知但现实的方面，并提供具体的经验，说明不确定性在真实结构分析中所起的作用。杜克大学的学生将定期访问该模型，以研究结构复杂性对传统结构分析主题(如影响线、弹性挠度的确定等)应用的影响。CMU的学生将研究类似的现象；但他们与模型的互动将通过互动网站进行。

Abstract:Within the last decade, structural identification(St-Id) has enjoyed increasing significance as a core and enabling concept for structural health monitoring (SHM), performance-based engineering (PBE), and asset management (AM) ? three paradigms that are now recognized by the US Congress, Federal Government Agencies and the ASCE as critical for improving infrastructure performance. The goal of St- Id is to infer un-measurable attributes of structural systems (e.g. boundary and continuity conditions, material stiffness, damage, etc) through the correlation of mathematical models and experimental response data. The underlying assumption is that there is a sufficient correlation between the measurable responses of the structure (e.g. displacement, strain, acceleration, etc.) and the desired un-measurable attributes, such that they can be inferred reliably. Although widely accepted, our present validation of this key assumption is provided nearly exclusively by anecdotal evidence and is neither comprehensive nor quantifiable (e.g. mode shapes are more sensitive than frequencies to damage). This knowledge gap both sustains a heavy reliance on user intuition and heuristics, and precludes reliable estimates of the total uncertainty (random and bias) associated with applications of St-Id.To address this knowledge gap, the proposed research is cast as a multivariate calibration in which the ability of various St-Id approaches to reliably infer changes in desired un-measurable attributes will be examined and quantified through the use of a probability-based ?identifiability index?, Id (analogous to the reliability index). This calibration will be carried out on a physical model in the laboratory at the Drexel Intelligent Infrastructure Institute (DI3), which was designed and constructed with similitude to common slab-on-girder bridges. To enable the control needed for this calibration, the model was fabricated with the ability to simulate several common boundary conditions, damage scenarios, and sources of structural complexities (e.g. local nonlinearities) as well as the ability to be configured with multiple levels of redundancies and irregularities (such as skew). Although the primary fundamental objective of this study is to determine the ?identifiability? of physics-based response indices (e.g. modal parameters) and non-physics- based models (e.g. neural networks), a secondary fundamental objective of identifying the ability of model updating procedures to infer absolute values of un-measurable attributes will also be satisfied.Intellectual Merit: The intellectual merit of this study lies in its aim to quantitatively establish the causal relationship between response indices/identified models and un-measurable attributes of constructed systems ? a relationship that serves as the underpinning for the St-Id process. While St-Id applications to date have provided some insight into this relationship, these insights are neither comprehensive nor quantitative in nature, which precludes their generalization. The authors believe that this knowledge gap represents a fundamental barrier to the extraction of reliable and widely applicable performance measures from constructed facilities, which hinders meaningful applications of SHM, PBE, and AM. The proposed effort will be the first attempt to rigorously investigate this relationship for constructed systems and represents a necessary first-step towards a more reliable and scientific form of St-Id.Broader Impacts: The proposed research will engage the St-Id community at large in the first damage detection benchmark study that explicitly represents realistic aspects of constructed facilities (e.g. structural complexities) as well as realistic approaches to acquiring data (e.g. ambient monitoring and crawl-speed truck testing). The results of this research will be broadly disseminated through newsletters, conferences and journals as well as through the development of an interactive website. The integrated educational component of this study will incorporate the physical model in the DI3 laboratory into undergraduate structural analysis courses at both Drexel and Carnegie Mellon Universities (DU and CMU). The objective of this effort will be to demonstrate less-understood but realistic aspects of the structural behavior of constructed systems and provide concrete experiences that illustrate the role uncertainty plays in the analysis of real structures. Students at DU will visit the model periodically to examine the impact of structural complexities on the application of traditional structural analysis topics such as influence lines, determination of elastic deflections, etc. Students at CMU will examine similar phenomena; however, their interaction with the model will be facilitated through the interactive website.Douglas A. Foutch, Program Director, Structural Systems and Hazard Mitigation of Structures