Scour is a cause of the failure and often subsequent collapse of many bridge structures. Therefore, owners and operators of hydraulic structures such as bridges need to appraise the scour risk to these important infrastructure assets. To determine if scouring has affected a bridge, visual inspection data is still commonly used by bridge engineers. However, this approach has various limitations, e.g. operations cannot be undertaken safely by human divers during flood events and visual inspection may sometimes yield inaccurate data about scour extent due to e.g. refilling of scour holes overtime. Early detection of the onset of scour can ensure time for intervention and for the planning of alternative transport routes and thus some of the network service losses during and immediately after extreme weather events can be avoided. To have access to reliable data on scour, it is important to specify and deploy monitoring equipment for detecting the rate and extent of scour. In this paper, an updated framework to assist engineers with the selection of the most suitable instrument or instruments for monitoring scour around riverine bridges is presented. The existence of different types of monitoring devices and approaches requires a framework for selecting the most proper device for a specific field site or sites, as each device has its benefits and challenges with regards to, for instance: purchasing costs; ease of installation; maintenance requirements; operational resilience against debris/ice and provision of accurate data. The proposed framework was developed after an extensive review of other scour monitoring device selection frameworks. Then a pilot study was conducted at the University of Bristol to refine the framework which has now been tested by undertaking a series of interviews with practitioners. The results of the preliminary testing of the new framework are presented in detail in this paper. The paper concludes with recommendations for how rating frameworks can be used as part of the efforts to transition to ‘smarter infrastructure’.

Urbanisation has led to urban population growth affecting the economy and the environment, including degrading air quality via pollution. Air pollution has been linked to a variety of conditions and health risks including heart disease, stroke, asthma, Alzheimer's and neurodevelopmental disorders. However, it is difficult for a citizen to find precise air pollution data at a particular location. Smart City strategies usually stipulate that city councils should focus on delivering platforms for active citizen participation using existing technology. Existing civic data hubs such as the London Datastore, Open Data Bristol etc., provide air pollution data but lack elaborate representations for user-defined locations. Existing air quality initiatives such as the Smart Citizen platform and Sensor.Community provide more advanced graphical representations. However, they restrict themselves to showing data coming from their respective devices. The paper presents the Open City Air Quality Platform (OpenCAQP), a development that merges a wide range of data sources and air pollution parameters into a single platform. The OpenCAQP allows citizens, environmentalists, data analysts, and developers to access and visualise data. The proposed solution contributes to two key objectives: i) analysis of the air pollution data sources available in a city; ii) a replicable scalable, modular open source capability aggregating and visualising air pollution data from multiple sources. Its effectiveness has been evaluated by measuring quality, usability and increased awareness of users through a feedback questionnaire.

AbstractDigitalisation and the Internet of Things (IoT) help city councils improve services, increase productivity and reduce costs. City‐scale monitoring of traffic and pollution enables the development of insights into low‐air quality areas and the introduction of improvements. IoT provides a platform for the intelligent interconnection of everyday objects and has become an integral part of a citizen's life. Anyone can monitor from their fitness to the air quality of their immediate environment using everyday technologies. With caveats around privacy and accuracy, such data could even complement those collected by authorities at city‐scale, for validating or improving policies. The authors explore the hierarchies of urban sensing from citizen‐to city‐scale, how sensing at different levels may be interlinked, and the challenges of managing the urban IoT. The authors provide examples from the UK, map the data generation processes across levels of urban hierarchies and discuss the role of emerging sociotechnical urban sensing infrastructures, that is, independent, open, and transparent capabilities that facilitate stakeholder engagement and collection and curation of grassroots data. The authors discuss how such capabilities can become a conduit for the alignment of community‐ and city‐level action via an example of tracking the use of shared electric bicycles in Bristol, UK.

This paper outlines project TwinERGY's suggested approach to collaborative mapping of emerging energy systems with relevant stakeholders, including in particular participant consumers. The approach is based on the use of the established Causal Loop Diagram (CLD) from within the remit of System Dynamics/System Thinking techniques, as the basis of group model building. We explain how CLD is a relevant modelling technique for the problem domain of energy systems and why its qualitative nature that highlights interdependencies makes it suitable for use with participant stakeholders. Finally, we illustrate modelling examples relevant to actual project testbed deployments and initial experiment scenarios with the use of the online CLD tool LOOPY.

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.

The use of problem structuring method (PSM) interventions leads to outcomes unique to the circumstances of the problem context. Given the singular nature of these outcomes, a consultant attempting to sell a PSM intervention will struggle to articulate value to clients in terms that are commercially meaningful prior to the intervention being enacted. Thus, in order to win a contract to deliver a PSM intervention, the consultant must first resolve this puzzle. We explore this question by (i) reviewing how the value of PSMs has been assessed previously, (ii) setting out a suitable theoretical position to explore the problem and (iii) presenting empirical data from a commercial organization to build our theoretical position. This starts with agreement with Checkland and Scholes that attempting to sell the (financial) value of a PSM intervention a priori is unlikely to ever succeed. Our theoretical development through analysis of empirical data leads to the recognition that the process of selling a PSM intervention is bound to the interposition of the processes of problematization and interessement and the issue of trust. The recognition of a distinction between these and the actual enactment of a PSM intervention leads us to conclude that the process of selling the consulting engagement is entirely associated with the temporal ordering between them. We thus avoid the bind of the original puzzle only by articulating a paradox. To resolve the paradox, we shift analytical focus to the pre‐contractual phase of the relationship between a consultant and client and discuss implications of this paradox for soft OR practice. © 2018 The authors. Systems Research and Behavioral Science published by International Federation for Systems Research and John Wiley & Sons Ltd

In order for an organization to meet its strategic objectives a change, in a combination of people, process or infrastructure, is often required. To enact this change an organizational design may be developed. There are currently many approaches to do this, however none take notice of intra-organizational issues. The organizational design approach introduced in this paper is a process that has been developed to drive the transition of an organization from its current to its future state, using systems principles. The process links the principles of established organizational design theory with problem structuring methods in order to support the delivery of organizational change within an engineering context.