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In this study, a technique using wireless impedance sensor node and interface washer is proposed for monitoring damage in structural connections of bridges. In order to achieve the objective, the following approaches are implemented. First, a wireless impedance sensor node is designed for automated and cost-efficient monitoring in structural connections. Second, impedance-based algorithms are embedded in the wireless impedance sensor node for autonomous monitoring of structural connections. Third, a tensile-force monitoring technique using an interface washer is proposed to overcome limitations of the wireless impedance sensor node such as measureable ranges with narrow frequency band, and the proposed technique is numerically validated. Finally, the performance of the wireless impedance sensor node and the interface washer is experimentally evaluated in cable-anchor connection and bolted connection models. [ABSTRACT FROM AUTHOR]

This paper aims to detect and locate damage in an innovative slab-on-girder pedestrian bridge model using the vibration characteristics determined from a combined experimental–numerical procedure. The innovative slab-girder pedestrian bridge model has a bi-layer composite deck with Glass Fiber Reinforced Polymer as the bottom layer and laminated glass as the top layer to exploit the desirable properties of these two materials. Modal data from experimental tests and numerical analyses of the bridge model under single and multiple damage cases together with the modal flexibility method are used to detect and locate damage in the bridge. Results show that the peaks of the model flexibility plots correctly locate the damage and that their values provide a good indication of damage severity, which depend on the number of damages, damaged member and location of damage. Results show that the early vibration modes of this bridge model are dominant in torsion, different to flexure dominant modes in traditional slab-girder bridges. Nevertheless, the combined experimental-numerical procedure is found to be effective for assessing both single and multiple damages in the innovative bridge model. The adopted procedure will be applicable to similar real bridge structures in future investigations and will contribute to their safety. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative pedestrian arch bridge, with a new bi-layer composite deck supported by a steel frame. Bottom and top layers of the bridge deck are composed of glass fibre reinforced polymer (GFRP) plate and laminated glass plate respectively. Structural evaluation of this aesthetically pleasing and lightweight pedestrian bridges is important to avoid excessive vibration. With this in mind, free vibration tests were first carried out on the proposed composite deck and results were used to validate a three-dimensional finite element (FE) model of the composite deck developed in ABAQUS software. Static and free vibration responses of the proposed pedestrian arch bridge with steel frame and composite deck are evaluated by FE analyses. While the static performance of the bridge was found to be satisfactory, the fundamental natural frequency was found to be within human walking frequency which could cause excessive vibration. Hence, further analysis was carried out by changing the cross-sectional areas of the bridge parts to obtain the desired performance of the bridge. Results were compared with recommended values in Bridge Design Code and they ensured that the proposed pedestrian arch bridge will be a safe, aesthetically pleasing and serviceable structure for the pedestrians. [ABSTRACT FROM AUTHOR]

Irrespective to how well structures were built, they all deteriorate. Herein, deterioration is defined as a slow and continuous reduction of structural performance, which if prolonged can lead to damage. Deterioration occurs due to different factors such as ageing, environmental and operational (E&O) variations including those due to service loads. Structural performance can be defined as load-carrying capacity, deformation capacity, service life and so on. This paper aims to develop an effective method to detect and locate deterioration in the presence of E&O variations and high measurement noise content. For this reason, a novel vibration-based deterioration assessment method is developed. Since deterioration alters the unique vibration characteristics of a structure, it can be identified by tracking the changes in the vibration characteristics. This study uses enhanced autoregressive (AR) time-series models to fit the vibration response data of a structure. Then, the statistical hypotheses of chi-square variance test and two-sample t -test are applied to the model residuals. To precisely evaluate changes in the vibration characteristics, an integrated deterioration identification (DI) is defined using the calculated statistical hypotheses and a Hampel filter is used to detect and remove false positive and negative results. Model residual is the difference between the predicted signal from the time series model and the actual measured response data at each time interval. The response data of two numerically simulated case studies of 3-storey and 20-storey reinforced concrete (RC) shear frames contaminated with different noise contents demonstrate the efficacy of the proposed method. Multiple deterioration and damage locations, as well as preventive maintenance actions, are also considered in these case studies. Furthermore, the method was successfully verified utilizing measured data from an experiment carried out on a box-girder bridge (BGB) structure. [ABSTRACT FROM AUTHOR]

Structural health monitoring data has been widely acknowledged as a significant source for evaluating the performance and health conditions of structures. However, a holistic framework that efficiently incorporates monitored data into structural identification and, in turn, provides a realistic life-cycle performance assessment of structures is yet to be established. There are different sources of uncertainty, such as structural parameters, computer model bias and measurement errors. Neglecting to account for these factors results in unreliable structural identifications, consequent financial losses, and a threat to the safety of structures and human lives. This paper proposes a new framework for structural performance assessment that integrates a comprehensive probabilistic finite element model updating approach, which deals with various structural identification uncertainties and structural reliability analysis. In this framework, Gaussian process surrogate models are replaced with a finite element model and its associate discrepancy function to provide a computationally efficient and all-round uncertainty quantification. Herein, the structural parameters that are most sensitive to measured structural dynamic characteristics are investigated and used to update the numerical model. Sequentially, the updated model is applied to compute the structural capacity with respect to loading demand to evaluate its as-is performance. The proposed framework's feasibility is investigated and validated on a large lab-scale box girder bridge in two different health states, undamaged and damaged, with the latter state representing changes in structural parameters resulted from overloading actions. The results from the box girder bridge indicate a reduced structural performance evidenced by a significant drop in the structural reliability index and an increased probability of failure in the damaged state. The results also demonstrate that the proposed methodology contributes to more reliable judgment about structural safety, which in turn enables more informed maintenance decisions to be made. [ABSTRACT FROM AUTHOR]