This proposal addresses the vital issue of prediction of multiphase flows in large diameter risers in off-shore hydrocarbon recovery. The riser is essentially a vertical or near-vertical pipe connecting the sea-bed collection pipe network (the flowlines) to a sea-surface installation, typically a floating receiving and processing vessel. In the early years of oil and gas exploration and production, the oil and gas companies selected the largest and most accessible off-shore fields to develop first. In these systems, the risers were relatively short and had modest diameters. However, as these fields are being depleted, the oil and gas companies are being forced to look further afield for replacement reserves capable of being developed economically. This, then, has led to increased interest in deeper waters, and harsher and more remote environments, most notably in the Gulf of Mexico, the Brazilian Campos basin, West of Shetlands and the Angolan Aptian basin. Many of the major deepwater developments are located in water depths exceeding 1km (e.g. Elf's Girassol at 1300m or Petrobras' Roncador at 1500-2000m). To transport the produced fluids in such systems with the available pressure driving forces has led naturally to the specification of risers of much greater diameter (typically 300 mm) than those used previously (typically 75 mm). Investments in such systems have been, and will continue to be, huge (around $35 billion up to 2005) with the riser systems accounting for around 20% of the costs. Prediction of the performance of the multiphase flow riser systems is of vital importance but, very unfortunately, available methods for such prediction are of doubtful validity. The main reason for this is that the available data and methods have been based on measurements on smaller diameter tubes (typically 25-75 mm) and on the interpretation of these measurements in terms of the flow patterns occurring in such tubes. These flow patterns are typically bubble, slug, churn and annular flows. The limited amount of data available shows that the flow patterns in larger tubes may be quite different and that, within a given flow pattern, the detailed phenomena may also be different. For instance, there are reasons to believe that slug flow of the normal type (with liquid slugs separated by Taylor bubbles of classical shape) may not exist in large pipes. Methods to predict such flows with confidence will be improved significantly by means of an integrated programme of work at three universities (Nottingham, Cranfield and Imperial College) which will involve both larger scale investigations as well as investigations into specific phenomena at a more intimate scale together with modelling studies. Large facilities at Nottingham and Cranfield will be used for experiments in which the phase distribution about the pipe cross section will be measured using novel instrumentation which can handle a range of fluids. The Cranfield tests will be at a very large diameter (250 mm) but will be confined to vertical, air/water studies with special emphasis on large bubbles behaviour. In contrast those at Nottingham will employ a slightly smaller pipe diameter (125 mm) but will use newly built facilities in which a variety of fluids can be employed to vary physical properties systematically and can utilise vertical and slightly inclined test pipes. The work to be carried out at Imperial College will be experimental and numerical. The former will focus on examining the spatio-temporal evolution of waves in churn and annular flows in annulus geometries; the latter will use interface-tracking methods to perform simulations of bubbles in two-phase flow and will also focus on the development of a computer code capable of predicting reliably the flow behaviour in large diameter pipes. This code will use as input the information distilled from the other work-packages regarding the various flow regimes along the pipe.

The international offshore energy industry is undergoing as revolution, adopting aggressive net-zero objectives and shifting rapidly towards large scale offshore wind energy production. This revolution cannot be done using 'business as usual' approaches in a competitive market with low margins. Further, the offshore workforce is ageing as new generations of suitable graduates prefer not to work in hazardous places offshore. Operators therefore seek more cost effective, safe methods and business models for inspection, repair and maintenance of their topside and marine offshore infrastructure. Robotics and artificial intelligence are seen as key enablers in this regard as fewer staff offshore reduces cost, increases safety and workplace appeal. The long-term industry vision is thus for a digitised offshore energy field, operated, inspected and maintained from the shore using robots, digital architectures and cloud based processes to realise this vision. In the last 3 years, we has made significant advances to bring robots closer to widespread adoption in the offshore domain, developing close ties with industrial actors across the sector. The recent pandemic has highlighted a widespread need for remote operations in many other industrial sectors. The ORCA Hub extension is a one year project from 5 UK leading universities with over 20 industry partners (>£2.6M investment) which aims at translating the research done into the first phase of the Hub into industry led use cases. Led by the Edinburgh Centre of Robotics (HWU/UoE), in collaboration with Imperial College, Oxford and Liverpool Universities, this multi-disciplinary consortium brings its unique expertise in: Subsea (HWU), Ground (UoE, Oxf) and Aerial robotics (ICL); as well as human-machine interaction (HWU, UoE), innovative sensors for Non Destructive Evaluation and low-cost sensor networks (ICL, UoE); and asset management and certification (HWU, UoE, LIV). The Hub will provide remote solutions using robotics and AI that are applicable across a wide range of industrial sectors and that can operate and interact safely in autonomous or semi-autonomous modes in complex and cluttered environments. We will develop robotics solutions enabling accurate mapping , navigation around and interaction with assets in the marine, aerial and ground environments that support the deployment of sensors for asset monitoring. This will be demonstrated using 4 industry led use cases developed in close collaboration with our industry partners and feeding directly into their technology roadmaps: Offshore Renewable Energy Subsea Inspection in collaboration with EDF, Wood, Fugro, OREC, Seebyte Ltd and Rovco; Aerial Inspection of Large Infrastructures in Challenging Conditions in collaboration with Barrnon, BP, Flyability, SLAMCore, Voliro and Helvetis; Robust Inspection and Manipulation in Hazardous Environments in collaboration with ARUP, Babcock, Chevron, EMR, Lafarge, Createc, Ross Robotics; Symbiotic Systems for Resilient Autonomous Missions in collaboration with TLB, Total Wood and the Lloyds Register. This will see the Hub breach into new sectors and demonstrate the potential of our technology on a wider scale.

The international offshore energy industry currently faces the triple challenges of an oil price expected to remain less than $50 a barrel, significant expensive decommissioning commitments of old infrastructure (especially North Sea) and small margins on the traded commodity price per KWh of offshore renewable energy. Further, the offshore workforce is ageing as new generations of suitable graduates prefer not to work in hazardous places offshore. Operators therefore seek more cost effective, safe methods and business models for inspection, repair and maintenance of their topside and marine offshore infrastructure. Robotics and artificial intelligence are seen as key enablers in this regard as fewer staff offshore reduces cost, increases safety and workplace appeal. The long-term industry vision is thus for a completely autonomous offshore energy field, operated, inspected and maintained from the shore. The time is now right to further develop, integrate and de-risk these into certifiable evaluation prototypes because there is a pressing need to keep UK offshore oil and renewable energy fields economic, and to develop more productive and agile products and services that UK startups, SMEs and the supply chain can export internationally. This will maintain a key economic sector currently worth £40 billion and 440,000 jobs to the UK economy, and a supply chain adding a further £6 billion in exports of goods and services. The ORCA Hub is an ambitious initiative that brings together internationally leading experts from 5 UK universities with over 30 industry partners (>£17.5M investment). Led by the Edinburgh Centre of Robotics (HWU/UoE), in collaboration with Imperial College, Oxford and Liverpool Universities, this multi-disciplinary consortium brings its unique expertise in: Subsea (HWU), Ground (UoE, Oxf) and Aerial robotics (ICL); as well as human-machine interaction (HWU, UoE), innovative sensors for Non Destructive Evaluation and low-cost sensor networks (ICL, UoE); and asset management and certification (HWU, UoE, LIV). The Hub will provide game-changing, remote solutions using robotics and AI that are readily integratable with existing and future assets and sensors, and that can operate and interact safely in autonomous or semi-autonomous modes in complex and cluttered environments. We will develop robotics solutions enabling accurate mapping of, navigation around and interaction with offshore assets that support the deployment of sensors networks for asset monitoring. Human-machine systems will be able to co-operate with remotely located human operators through an intelligent interface that manages the cognitive load of users in these complex, high-risk situations. Robots and sensors will be integrated into a broad asset integrity information and planning platform that supports self-certification of the assets and robots.

This proposal addresses the vital issue of prediction of multiphase flows in large diameter risers in off-shore hydrocarbon recovery. The riser is essentially a vertical or near-vertical pipe connecting the sea-bed collection pipe network (the flowlines) to a sea-surface installation, typically a floating receiving and processing vessel. In the early years of oil and gas exploration and production, the oil and gas companies selected the largest and most accessible off-shore fields to develop first. In these systems, the risers were relatively short and had modest diameters. However, as these fields are being depleted, the oil and gas companies are being forced to look further afield for replacement reserves capable of being developed economically. This, then, has led to increased interest in deeper waters, and harsher and more remote environments, most notably in the Gulf of Mexico, the Brazilian Campos basin, West of Shetlands and the Angolan Aptian basin. Many of the major deepwater developments are located in water depths exceeding 1km (e.g. Elf's Girassol at 1300m or Petrobras' Roncador at 1500-2000m). To transport the produced fluids in such systems with the available pressure driving forces has led naturally to the specification of risers of much greater diameter (typically 300 mm) than those used previously (typically 75 mm). Investments in such systems have been, and will continue to be, huge (around $35 billion up to 2005) with the riser systems accounting for around 20% of the costs. Prediction of the performance of the multiphase flow riser systems is of vital importance but, very unfortunately, available methods for such prediction are of doubtful validity. The main reason for this is that the available data and methods have been based on measurements on smaller diameter tubes (typically 25-75 mm) and on the interpretation of these measurements in terms of the flow patterns occurring in such tubes. These flow patterns are typically bubble, slug, churn and annular flows. The limited amount of data available shows that the flow patterns in larger tubes may be quite different and that, within a given flow pattern, the detailed phenomena may also be different. For instance, there are reasons to believe that slug flow of the normal type (with liquid slugs separated by Taylor bubbles of classical shape) may not exist in large pipes. Methods to predict such flows with confidence will be improved significantly by means of an integrated programme of work at three universities (Nottingham, Cranfield and Imperial College) which will involve both larger scale investigations as well as investigations into specific phenomena at a more intimate scale together with modelling studies. Large facilities at Nottingham and Cranfield will be used for experiments in which the phase distribution about the pipe cross section will be measured using novel instrumentation which can handle a range of fluids. The Cranfield tests will be at a very large diameter (250 mm) but will be confined to vertical, air/water studies with special emphasis on large bubbles behaviour. In contrast those at Nottingham will employ a slightly smaller pipe diameter (125 mm) but will use newly built facilities in which a variety of fluids can be employed to vary physical properties systematically and can utilise vertical and slightly inclined test pipes. The work to be carried out at Imperial College will be experimental and numerical. The former will focus on examining the spatio-temporal evolution of waves in churn and annular flows in annulus geometries; the latter will use interface-tracking methods to perform simulations of bubbles in two-phase flow and will also focus on the development of a computer code capable of predicting reliably the flow behaviour in large diameter pipes. This code will use as input the information distilled from the other work-packages regarding the various flow regimes along the pipe.

Engineered systems are increasingly being used autonomously, making decisions and taking actions without human intervention. These Autonomous Systems are already being deployed in industrial sectors but in controlled scenarios (e.g. static automated production lines, fixed sensors). They start to get into difficulties when the task increases in complexity or the environment is uncontrolled (e.g. drones for offshore windfarm inspection), or where there is a high interaction with people and entities in the world (e.g. self-driving cars) or where they have to work as a team (e.g. cobots working in a factory). The EN-TRUST Vision is that these systems learn situations where trust is typically lost unnecessarily, adapting this prediction for specific people and contexts. Stakeholder trust will be managed through transparent interaction, increasing the confidence of the stakeholders to use the Autonomous Systems, meaning that they can be adopted in scenarios never before thought possible, such as doing the jobs that endanger humans (e.g. first responders or pandemic related tasks). The EN-TRUST 'Trust' Node will perform foundational research on how humans and Autonomous Systems (AS) can work together by building a shared reality, based on mutual understanding through trustworthy interaction. The EN-TRUST Node will create a UK research centre of excellence for trust that will inform the design of Autonomous Systems going forward, ensuring that they are widely used and accepted in a variety of applications. This cross-cutting multidisciplinary approach is grounded in Psychology and Cognitive Science and consists of three "pillars of trust": 1) computational models of human trust in AS; 2) adaptation of these models in the face of errors and uncontrolled environments; and 3) user validation and evaluation across a broad range of sectors in realistic scenarios. This EN-TRUST framework will explore how to best establish, maintain and repair trust by incorporating the subjective view of human trust towards Autonomous Systems, thus maximising their positive societal and economic benefits.