Summary The process for assessing the condition of a bridge involves continuously monitoring changes to the material properties, support conditions, and system connectivity throughout its life cycle. It is known that the structural integrity of bridges can be monitored by measuring their vibration responses. However, the relationship between frequency changes and structural damage is still not fully understood. This study presents a bridge condition assessment framework which integrates computational modelling and noncontact radar sensor techniques (i.e., IBIS‐S) to predict changes in the natural frequencies of a bridge girder as a result of a range of parameters that govern its structural performance (e.g., elastomeric bearing stiffness, concrete compressive stiffness, and crack propagation). Using a prestressed concrete bridge in Australia as a case study, the research outcomes suggest that vibration monitoring using IBIS‐S is an efficient way for detecting the degradation of elastomeric bearing stiffness and shear crack propagation in the support areas that can significantly affect the overall structural integrity of a bridge structure. However, frequency measurements have limited capability for detecting the decrease in the material properties of a bridge girder.

Bridges play an important role in economic development and bring important social benefits. The development of innovative bridge monitoring techniques will enable road authorities to optimize operational and maintenance activities for bridges. However, monitoring the dynamic behavior of a bridge requires a comprehensive understanding of the interaction between the bridge and traffic loading which has not been fully achieved so far. In the present study, an integrated bridge health monitoring framework is developed using advanced 3D Finite Element modeling in conjunction with Weight-in-motion (WIM) technology and interferometric radar sensors (IBIS-S). The realistic traffic loads imposed on the bridge will be obtained through calibration and validation of traffic loading prediction model using real-time bridge dynamic behavior captured by IBIS-S and WIM data. Using the Merlynston Creek Bridge in Melbourne, Australia as a case study, it demonstrated that the proposed bridge monitoring framework can both efficiently and accurately capture the real-time dynamic behavior of the bridge under traffic loading as well as the dynamic characteristics of the bridge. The outcomes from this research could potentially enhance the durability of bridges which is an important component of the sustainability of transport infrastructure.

The maintenance and operation of bridges represent a significant investment in both the public and private domains. In practice, the structural damage of a bridge that accumulates over its life-span is a result of continuous degradation caused mainly by traffic conditions and sudden extreme events (e.g. flooding, fires and severe traffic accidents). However, under heavy truck loading, the deterioration rate of a bridge can be accelerated. As the use of heavier articulated trucks becomes increasingly popular in contemporary freight transportation systems, the development of modern Non-Destructive Testing (NDT) techniques in conjunction with computational modelling becomes necessary. The advancement in this area will allow rapid assessment of the structural health of bridges and detection of ongoing damage to enhance the structural performance of bridges.

This paper presents an integrated framework for structural health monitoring of bridges by using advanced non-destructive testing (NDT) technique in conjunction with computational modelling. First, the structural characteristics of the Eltham Trestle Bridge under train loading were monitored using the combination of the 3D optical measurement system and IBIS-S. The results demonstrate that, in conjunction with computational modelling, the NDT can capture the structural health conditions of the bridge by analysing the natural frequencies and deformation profiles of the critical members of the bridges. Then, the developed framework also takes into account the impact of extreme events (e.g. truck impacts and earthquakes) by using a reliability-based model. Finally, using the Montague Street Bridge as a case study, it shows that proposed framework has the capability of predicting the residual life of a bridge subject to both progressive deterioration and extreme events throughout its service life.

<p>Structural degradation caused by sudden damaging extreme events (<em>e.g. </em>earthquake) has significant impact on residual life of bridges and ultimately the collapse of bridges. This paper presents a reliability-based approach of a bridge subjected to shock degradation caused by earthquake events. In particular, this study develops a numerical procedure for assessing time dependent probability of failure to estimate the residual life a bridge. Key factors that govern the residual life of a bridge (e.g., damage size caused by earthquake shocks and loss of initial structural capacity) were investigated. The results of study show that both damage size caused by earthquake shocks and loss of initial structural capacity are key factors that govern residual life of a bridge.</p><p> </p><p>Keywords: <em>residual life, earthquake, shock degradation, bridge</em>.</p>

Bridges are a critical part of transport infrastructure networks for social activities and economics of human life. Dynamic analysis of bridge is very important to perform in order to ensure the ability of the bridge to withstand loads and maintain the sustainability of transport infrastructure. This paper presents a methodological framework for monitoring dynamic behavior of the bridge (e.g., natural frequencies, displacement time history) by using civil engineering micro-tremor technique and numerical modeling. The study was conducted at the Alue Raya Bridge located in Lhokseumawe City, Aceh Province, Indonesia. To capture the dynamic behavior of the bridge under traffic loading, the micro-tremor techniques, e.g., Short Period Seismograph (SPS) sensor was placed underneath the bridge at the mid span of the bridge girder. The obtained vibration data were processed using Geopsy software. A three dimensional (3D) model of the bridge was then developed by using CSI Bridge software. The modal analysis was conducted to obtain the modal natural frequencies of the bridge due to traffic loads. The natural frequency measurements using SPS were compared with the simulation results. Through analyzing the measured results, it was found that the natural frequency of the bridge is around 4,3275 Hz which is very close to those obtained from numerical modeling using CSI bridge software. The measured maximum vertical displacement of the bridge girders is below 5mm under normal traffic condition which is under the allowable serviceability limit state requirements of the bridge. The outcomes of this study could have the potential to enable maintenance and capital works decisions which are an important component of the sustainability of transport infrastructure.

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