Inspections of engineered structures below water level are essential to ensure the long-term serviceability of bridge infrastructure and to avoid major damage or failure. This research aimed to investigate integrated geophysical technologies for the underwater inspection of bridge foundation-related scour and erodible scour-based infill. Survey methods focused on Water-Penetrating Radar (WPR), supplemented by sonar. Whilst the survey benefits of the sonar imaging water–sediment interface and structures are well known, those of WPR are not. However, it is ideally suited to the survey of the water base and sub-sediment in shallow (>10 m) freshwater, especially where suspended sediment, weed infestation or methane impede sonar results. Our work produced good WPR imagery acquired from small, manoeuvrable boats that allowed bathymetric profiles to be plotted, as well as the likely locations of soft-sediment scour in future high-water flow events. This study provides clear benefits for integrated sonar and WPR surveys in the quantitative assessment of engineered structures within freshwater.

Ground‐penetrating radar (syn. water‐penetrating radar, or WPR hereon) has been used previously in the detection and characterisation of riverine scour. This paper presents field data, equipment calibration and processing output results from a new generation of high dynamic range (HDR) radar systems. These provide a new and more sophisticated model of fluvial scour for the study site. The adaptability for deployment on water, wide bandwidth and good quality in raw and processed data, demonstrates the advantages of the system. Data processing and depth calibration are issues in the interpretation of WPR data, which are both discussed. WPR demonstrates the potential for surveying sedimentation where palaeoscour occurred and thus anticipated. This maybe in conjunction with other techniques or where aquatic vegetation, rocky substrates or methane gas bubble release preclude use of sonar.

The ability to effectively manage the deterioration of a network-wide bridge stock condition from year to year is vital for the effective use of finite resources while maintaining public safety. The leading cause of bridge failures and deterioration globally is bed scour. This paper looks at the development of a novel fibre Bragg grating (FBG) vortex flow sensor (VFS) for scour, utilising vortex-induced vibration flow effects. These sensors can provide early warnings to bridge managers and allow for a proactive approach to scour management at vulnerable bridges. This paper briefly reviews the current types of scour sensors available before outlining the initial development of the novel VFS set-up and associated prototype development. The initial findings of laboratory trials are presented before outlining the selection process for a masonry arch bridge test site.

This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up nearly 56% of the total bridge stock in NI. This initial analysis aims to identify trends that might help inform maintenance decisions in the future. Consideration of the Bridge Condition Indicator (BCI) average value for the overall arch bridge stock indicates the potential for regional variations in the overall condition and the potential for human bias in inspections. The paper presents the most prevalent structural elements and associated defects recorded in the inspections of arch bridges. This indicated a link to scour and undermining for the worst-conditioned arch bridges. An Analysis of Variance (ANOVA) analysis identified function, number of spans, and deck width as significant factors during the various deterioration stages in a bridge’s lifecycle.

Structural Health Monitoring (SHM) systems can support bridge maintenance decisions using performance data from sensors to supplement traditional inspections. Population-based SHM (PBSHM) further aims to leverage data from multiple source structures to improve the understanding and decision process for a target or group of target structures. Part of PBSHM research relates to understanding how structures within a group, or population, are similar to one another using a quantitative metric. Since similarity between bridges does not suffice for direct comparison of responses to the different loads they experience, a normalisation process using the same loading is required.,The research presented in this paper investigates whether a population of beam-and-slab bridges, that have been identified as similar using irreducible element (IE) models and developed graph-matching methods to calculate a similarity score, will also exhibit similar responses to known loading. Specifically, for this group of bridges this research shows that the displacement responses are comparable for the same laden vehicle. While intuitive, the hypothesis needs to be tested. To enable the comparison via accurate field-measured displacements obtained indirectly using accelerometers, a novel integration procedure was developed, mitigating effects of low-frequency sensor noise in acceleration response prior to double integration to bridge displacement. This enabled the direct comparison, validating the population-based approach for estimating response to static loading without direct measurement.