Visual inspection remains an essential tool for assessing structural damage. Damage detection is a challenging task for those specifying, designing, and deploying SHM systems. Often only traditional visual inspection processes are available to determine the type and extent of structural damage. For bridge structures in the UK, a regime of general (every two years) and principal (every six years) inspections is often followed. Such visual inspections are time-consuming and costly in terms of both labour and financial resources. Therefore, the possibility of completing more of the bridge visual inspection process offsite has many potential benefits for bridge owners and managers during the service life of the asset. Recent research conducted at the University of Bristol in collaboration with industrial partners has examined how to make the best use of metrics derived from visual inspection data when assessing bridge condition and planning maintenance activities. Recent research into which aspects of the current visual inspection regime in the UK could potentially be moved offsite has also been carried out. This paper summarises these research efforts and discusses how AI may be used as part of future enhancements to visual inspection data capture and analysis.

Hydraulic actions resulting in scour are a major cause of bridge failures worldwide. The development of scour is affected by various factors including structural geometry, river morphology and weather conditions. Detection of scour is often carried out using visual inspection-based methods. Visual inspection requires the expertise of divers which incurs high levels of risk, especially during times of high-water flow. Therefore, sensing technologies are becoming increasingly popular with the aim to supplement or replace higher risk visual inspection approaches. Specification of Structural Health Monitoring (SHM) systems is an important activity for bridge engineers and asset managers. This activity can be assisted by SHM rating frameworks, the use of which gives evidence to support specification of monitoring systems for individual bridges. In this paper, three previously published scour rating frameworks are compared using a bridge case study database.

The visual inspection of bridges is a major undertaking for asset owners and operators. In the UK, visual inspections require inspectors to visit bridges on site and often at night and under unfavourable weather conditions. Therefore, it would be beneficial to move some of the visual inspection process off site. This paper studies whether the defect classification aspects of the inspection process could be conducted remotely using photographs. This study examines the defect ratings assigned by ten survey participants who were tasked with examining photographs from visual inspections of ten UK bridges. The survey results were compared with the results from the general inspections previously carried out for the bridges in question. From this data set, the differences in the ratings given and the extent to which defects are missed were examined. The results show that a higher number of defects were identified for a given bridge by the remote inspectors. Statistical analysis shows that aggregated defects rated by off-site inspectors tend to be more severe and of a higher priority rating compared with those from the on-site inspectors. The results also indicate that there is closer agreement between on-site and off-site inspectors for defects of a higher severity rating.

Scour is a significant cause of bridge failure, and resulting bridge closures are likely to generate significant disruption to infrastructure networks. The management of scour-susceptible bridges is a significant challenge for improving transport resilience, but tends to be heuristic and qualitative. Such assessments often suffer from insufficient knowledge of key factors and require assumptions, which may increase their estimation and relative uncertainty. Analysis of publicly available technical documents reveals that various definitions of “risk” are adopted, as well as multiple approaches are applied. This paper has three objectives: (i) to illustrate the concept of risk in bridge scour management; (ii) to propose a simple scoring system to analyse existing risk-based approaches to manage bridge scour; and (iii) to analyse and compare such approaches on the basis of the obtained scores. A sample of nine documents containing bridge scour risk assessment practices or approaches was analysed using the developed rating system.

Visual inspection remains key for assessing the condition of bridges and hence assisting with planning and maintenance activities. There have been many efforts to improve or supplement visual inspection processes using new sensing technologies and data capture methods to usher in an era of 'smart bridges' or 'smart infrastructure'. One method to improve data capture is a 'remote inspection' where inspectors use digital photographs of a bridge to identify and grade structural defects to the standard of a 'General inspection' (GI). In this paper, survey data is presented to help formulate a preliminary assessment of the potential for engineers to implement this possible evolution of the visual inspection process. A potential Schema for remote visual inspections is developed and presented as a conceptual web application. The focus on the development of the Schema includes the need for ease of use by inspectors and integration of collected digital data into bridge management systems. The suggested platform is seen as a transitional method to aid in the long-term implementation of further automation of the inspection process. The system architecture is provided along with possible technologies that may support or enhance it, as well as a discussion of the potential barriers to implementation.

Bridge scour is a complex bridge-management problem. It is also a difficult forensic engineering challenge, as the greatest risk occurs during large flows and flood events, when visual inspection of the bridge piers is often not possible. This paper presents a review of scour prediction and modelling methods, whose results are used to determine the key parameters that scour-monitoring systems need to capture. Then, a review of existing monitoring approaches and technologies for scour monitoring is presented. The paper concludes with the proposal of a novel rating system for evaluating different scour-monitoring techniques. The new rating system is trialled ex-post for seven previously published bridge-scour-monitoring case studies to illustrate the use of the new methodology.

Scour is a major cause of bridge failure and results in significant economic losses through disruption to operation. This phenomenon naturally affects bridges with underwater foundations and is exacerbated during high river and/or turbulent flows (e.g. due to extreme events). When scour reaches the bottom of or undermines shallow foundations, it may trigger various damage mechanisms that may influence the safety of the structure and force asset managers to reduce traffic capacity. Currently, assessing risk of scour is a heuristic process, heavily reliant on qualitative approaches and expert opinion (e.g. visual inspections). These types of assessments typically suffer from insufficient knowledge of influencing factors (e.g. hydraulic parameters) and the requirement to rely on several assumptions (e.g. assumed foundation depth). As a result, current scour assessment and bridge management practices do not provide reliable solutions for addressing the potential risk of bridge failures. In this paper, cross-cutting needs and challenges related to the development of decision support tools for scour-risk management are highlighted and some preliminary results of a literature survey are reported. The review has been performed with several objectives: (i) identifying scour-risk indicators describing hydrodynamic actions and the asset condition; (ii) defining indirect and direct consequences needed to assess the risks associated to different decision alternatives related to scour management; and (iii) identifying existing approaches to scour inspections and monitoring as support tools for informed decisions. The results of this survey will serve as a base for future research aimed to develop an informed decision support tool to manage scour risk at both the bridge and at the network level.