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 (www.nees.org).
