Abstract

As a result of the recent advances in sensors, information technologies and materialscience, a considerable amount of research has been conducted in the area of smartinfrastructures. While there are many important components of a smart infrastructure,an automated and continuous structural health monitoring (SHM) system is acritical one. SHM is typically used to track and evaluate the performance of astructure, symptoms of operational incidents, anomalies due to deterioration anddamage during regular operation as well as after an extreme event. Successful healthmonitoring applications can be achieved by integrating experimental, analyticaland information technologies on real-life operating structures. However, real-lifeinvestigations must be backed up by laboratory benchmark studies for validatingtheory, concepts, and new technologies. For this reason, a physical bridge model isdeveloped to implement SHM methods and technologies. In this study, differentaspects of model development are outlined in terms of design considerations,instrumentation, finite element modeling, and simulating damage scenarios. Differentdamage detection methods are evaluated using the numerical and the physicalmodels. Modal parameter estimation studies are carried out to reliably identifythe eigenvalues, eigenvectors and modal scaling from the measurement data. Toassess the simulated damage, modal flexibility-based displacements and curvaturesare employed. Structural behavior after damage is evaluated by inspecting thedeflected shapes obtained using modal flexibility. More localized damage simulationssuch as stiffness reduction at a joint yield a very subtle stiffness decrease. In thiscase, the writers use a baseline to identify damage and also investigate the useof curvature as a complementary index. Curvature is advantageous for certaincases where the displacement results do not provide substantial changes. Issuesrelated to using curvature as a damage identification index are also addressed.

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