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.

Digital Twins (DTs) are forecasted to be used in two-thirds of large industrial companies in the next decade. In the Architecture, Engineering and Construction (AEC) sector, their actual application is still largely at the prototype stage. Industry and academia are currently reconciling many competing definitions and unclear processes for developing DTs. There is a compelling need to establish DTs as practice in AEC by developing common procedures and standards tailored to the sector's procedures and use cases. This paper proposes a step-by-step workflow process for developing a DT for an existing asset in the built environment, providing a proof-of-concept case study based on the Clifton Suspension Bridge in Bristol (UK). To achieve its aim, this paper (i) reviews the state-of-the-art of DTs in Civil Engineering, (ii) proposes a working DT-based workflow framework for the built environment applicable to existing assets, (iii) applies the framework and develops of the physical-virtual architecture to a case study of bridge management, and finally (iv) discusses insights from the application. The main novelty lies in the development of a versatile methodological framework that can be applied to the broad context of civil infrastructure. This paper's importance resides in the knowledge challenge, value proposition and operation dictated by developing a DT workflow for the built environment, which ultimately represents a relevant use case for the digital transformation of national infrastructure.

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.

Bridges are crucial points of connection in the transport system, underpinning economic vitality, social well-being and logistics of modern communities. Bridges have also strategic relevance, since they support access to emergency services (e.g. hospitals) and utilities (e.g. water supply). Bridges are mostly exposed to natural hazards, in particular riverine bridges to flooding, and disruption could lead to widespread negative effects. Therefore, protecting bridges enhances the resilience of cities and communities. Currently, most of the countries are not able to identify bridges at higher risk of failure, due to the unavailability of high-quality data, the mixed ownership of the assets or the lack of risk-based assessment approaches. Moreover, current datasets are not accommodating new data deriving from monitoring systems and other technologies. This paper introduces a risk-based approach to bridge management, alongside a preliminary protocolled taxonomy for data collection of bridges.

Society is dependent on aging infrastructure, which usually operates outside its expected life. Replacing this infrastructure is often an unviable option due to its cost and disruption. A structure's operational life might be extended if the features of its aging are better understood, enabling preventive maintenance to compensate. Digital Twins (the continuous comparison between sensor measurements and a mathematical model) are one way of enabling this sort of data-driven decision making. However, despite the possibilities for this technology, its take up amongst industry has been slow, in part because infrastructure managers are unsure of how the technology will support them. This work develops a methodological framework to enhance this uptake in the field of systems engineering and the system development life cycle, using the developed knowledge to inform how an operational Digital Twin should be created. The requirements capture is the most important part of any system design development process. We present a Digital Twin development method, grounded firmly in a thorough requirements capture, and illustrate how those requirements inform many of the later design decisions. We then present our method through a case study of the Clifton Suspension Bridge, UK. Our method provides a series of actionable steps, the completion of which will facilitate the creation of a Digital Twin able to support operational decisions. By fulfilling the requirements of infrastructure managers, we hope to encourage the uptake of the technology.