NEESR Payload: Damage Detection of Reinforced Concrete Columns Subjected to Combined Actions

该奖项是国家科学基金会07-506计划征求题为“乔治E。小布朗地震工程模拟网络（NEES）研究。该项目是美国国家科学基金会0530737奖的有效载荷项目，题为“NEESR SG：地震模拟和设计的桥梁柱在组合作用下，和系统响应的影响。“该项目将利用位于伊利诺伊大学厄巴纳-香槟分校和里诺的内华达州大学的NEES设备站点，以及位于罗拉的密苏里州大学的结构实验室。 该有效载荷项目的两个主要目标是：（1）验证项目研究人员开发的智能骨料技术，用于动态、伪动态和反向循环载荷条件下钢筋混凝土柱的损伤检测，以及（2）通过将基于智能骨料的损伤指数与损伤之间的相关性，矩阵与传统方法的结果，如目视检查和应变片测量。智能骨料由一个压电传感器/致动器封装在一个小的混凝土保护圆筒。基于压电陶瓷的智能骨料是多功能的，可以执行损伤检测的帮助下，开发的损伤指数和损伤指数矩阵。 迄今为止，这种方法仅在静态载荷条件下通过实验进行了验证。为了进一步验证智能骨料的功能，损伤检测，重要的是在不同的加载条件下进行实验，如动态，伪动态，和反向循环加载。这些智能骨料可以很容易地集成到根据美国国家科学基金会奖CMMI-0530737的测试建造的钢筋柱。这项研究的结果将用于开发小学和高中，本科和研究生水平的教育模块使用智能材料作为传感器。这项研究的结果将影响土木工程项目中创新材料的实施策略。 该项目的数据将通过NEES数据储存库（http：//www.example.com）提供。www.nees.org

This award is an outcome of the National Science Foundation 07-506 program solicitation entitled "George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES) Research." This project is a payload project to National Science Foundation award 0530737 entitled "NEESR SG: Seismic Simulation and Design of Bridge Columns under Combined Actions, and Implications on System Response." This project will utilize the NEES equipment sites located at the University of Illinois at Urbana-Champaign and the University of Nevada, Reno, as well as the structural laboratory at the University of Missouri, Rolla. The two major objectives of this payload project are (1) to verify smart aggregate technology, which has been developed by the project investigators, for damage detection of reinforced concrete columns under dynamic, pseudo-dynamic, and reverse-cyclic loading conditions, and (2) to quantitatively study damage on the reinforced columns under these three different loading conditions by correlating the smart aggregate based damage index and damage matrix with results from conventional methods such as visual inspection and measurements from strain gauges. A smart aggregate consists of a piezoelectric sensor/actuator encased in a small protective cylinder of concrete. The piezoceramic based smart aggregates are multi-functional and can perform damage detection with the help of a developed damage index and a damage index matrix. This approach has been verified to date by experiments under static loading conditions only. To further validate the functionalities of smart aggregates for damage detection, it is important to conduct experiments under different loading conditions, such as dynamic, pseudo-dynamic, and reverse-cyclic loadings. These smart aggregates can be easily integrated into the reinforced columns constructed for testing under National Science Foundation award CMMI-0530737.Outcomes of this research will be used to develop elementary and high school, undergraduate, and graduate level educational modules about the use of smart materials as sensors. Results from this research will impact implementation strategies for innovative materials in civil engineering projects. Data from this project will be made available through the NEES data repository (http://www.nees.org).