Assessment of structural health of an existing prestressed concrete bridge by finite element analysis

Abstract

This study investigates the feasibility of an alternative structural health monitoring (SHM) technique for an existing, post-tensioned, prestressed concrete bridge in Niigata, Japan. Currently, a static SHM system is in place to detect the progress of damages within the bridge. However, the existing system cannot properly monitor the structural health of the bridge including the periodic vibration, which is one of the damage-sensitive features of interest. Therefore, to effectively detect the real-time performances of the bridge, a three-dimensional (3D) Finite Element (FE) model was developed as a reference and verified using on-site loaddeflection test results. After validating the reference FE model, different damage scenarios, such as degradation of concrete, corrosion & rupture of steel tendons and missing tendons, were incorporated in the FE models. Based on non-linear structural and Eigenvalue analyses, natural frequencies and mode shapes of the bridge remain constant even after careful consideration of all types of damages in the FE model. However, vertical displacements are observed to increase for the damage scenarios. Although the effect of tendon rupture and corrosion showed negligible influences on the vertical displacement, the deterioration of the concrete largely influenced the vertical displacement. Additionally, crack widths were found to vary with damage types. Brifely, this study recommends some effective indicators to monitor the structural conditions of the bridge using FE analysis (FEA).

Finite-Element Performance Degradation Behavior of a Suspension Prestressed Concrete Arch Bridge with Grouting Defects

“…For prestressed concrete bridges, it is common for the midpoint to represent the structurally weakest point of the girder. Notably, this location often exhibits significant vertical displacement when subjected to unpredictable damage [33,34]. Hence, the impacts of concrete shrinkage, creep, and the corrosion of steel strands on the midpoint vertical displacement of the girder needed to be analyzed.…”

Structural Health Monitoring of a steel truss railway bridge studying its low frequency response

“…Focusing on direct approaches, a further classification can be done depending on the frequency range of interest, distinguishing between static and quasi-static analysis (low frequency range) and dynamic analysis (high frequency range). With regards to the data analysis framework, instead, a distinction can be made between modelbased approaches (e.g., [6]) and data-driven ones [7]. While the second allows the detection of anomalies in the bridge behaviour without the need of a structural model, the first allows for a physical interpretation of the anomalies identified by the monitoring system, but it requires a proper estimation of model parameters and model validation.…”