Foundation scour is a major issue affecting the structural safety of existing bridges, hence its monitoring is of paramount importance. This paper reports a case history of assessment and monitoring with dynamic tests for a bridge affected by scouring and subjected to retrofitting. Two different approaches measuring traffic-induced vibrations are applied as potential tools for monitoring foundation scour. The modal identification of bridge spans is one approach, and the observation of the dynamic response of pier foundations is the other approach. A finite-element model is used to choose the parameters for scour monitoring. Both approaches are applied to the experimental data collected about the structure prior to and after retrofitting to show their effectiveness.

Measuring the response of a structure to the ambient and service loads is a source of information that can be used to estimate some important engineering parameters or, to a certain extent, to characterize the structural behavior as a whole. By repeating the data acquisition over a period of time, it is possible to check for variations in the structure’s response, which may be correlated to the appearance or growth of a damage (e.g. following some exceptional event as the earthquake, or as a consequence of materials and components aging). The complexity of some existing structures and their environment very often requires the execution of a monitoring plan in order to support analyses and decisions through the evidence of measured data. If the monitoring is implemented through a sensor network continuously acquiring over time, then the evolution of the structural behavior may be tracked continuously as well. Such approach has become a viable option for practical applications since the last decade, as a consequence of the progress in the data acquisition and storage systems. However, proper methods and algorithms are needed for managing the large amount of data and the extraction of valuable knowledge from it. This article presents a methodology aimed at making automatic the process of structural monitoring in case it is carried continuously over time. It relies on some existing methods from the machine learning and data mining fields, which are casted into a process targeted to delimit the need of the human being intervention to the training phase and the engineering judgment of the results. The methodology has been successfully applied to the real-world case of an ancient masonry bell tower, the Ghirlandina Tower (Modena, Italy), where a network made of 12 accelerometers and 3 thermocouples has been acquiring continuously since August 2012. The structural characterization is performed by identifying the first modes of vibration, whose evolution over time has been tracked.

The heritage of existing road infrastructures and in particular of bridges consists of structures that are approaching or exceeding their designed service life. Detrimental causes such as aging, fatigue and deterioration processes other than variation in loading conditions introduce uncertainties that make structural assessment a challenging task. Experimental data on their performances are crucial for a proper calibration of numerical models able to predict their behavior and life-cycle structural performance. In this scenario, an experimental research program was established with the aim of investigating a set of 50-year-old prestressed concrete bridge girders that were recovered from a decommissioned bridge. The activities included initial non-destructive tests, and then full-scale load tests followed by a destructive test on the material samples. This paper reports the experimental results of the full-scale tests conducted on the first group of four I-beams assumed to be in good condition from visual inspection at the time of testing. Loading tests were performed using a specifically designed steel reaction frame and a test setup equipment, as detailed in the present work. Due to the structural response of this first group of girders, a uniform behavior was found at both service and ultimate conditions. The failure mechanism was characterized by the crushing of the cast-in-situ top slab corresponding to a limited deflection, highlighting a non-ductile behavior. The outcomes of the experimental research are expected to provide new data for the life-cycle safety assessment of existing bridges through an extended database of validated experimental tests and models.

Historical masonry towers survive at an alarming angle of inclination and may be in danger of leaning instability due to the lack of stiffness of the supporting soil. Therefore, careful investigation is required to estimate the seismic vulnerability as well as its long-term behavior. These problems require a multidisciplinary approach to properly model the behavior of the structure and its interaction with the supporting soil. This article is intended to contribute to these aspects, by showing how identification analyses can highlight the role of soil–structure interaction, and focuses on the model-updating techniques to forecast its behavior under seismic events.