
FundRef: 501100001174 , 501100001197 , 501100004511 , 501100001801
RRID: RRID:SCR_012342 , RRID:nlx_74663
ISNI: 0000000419367910
Wikidata: Q1517021
FundRef: 501100001174 , 501100001197 , 501100004511 , 501100001801
RRID: RRID:SCR_012342 , RRID:nlx_74663
ISNI: 0000000419367910
Wikidata: Q1517021
This proposal is for a new EPSRC Centre for Doctoral Training in Wind and Marine Energy Systems and Structures (CDT-WAMSS) which joins together two successful EPSRC CDTs, their industrial partners and strong track records of training more than 130 researchers to date in offshore renewable energy (ORE). The new CDT will create a comprehensive, world-leading centre covering all aspects of wind and marine renewable energy, both above and below the water. It will produce highly skilled industry-ready engineers with multidisciplinary expertise, deep specialist knowledge and a broad understanding of pertinent whole-energy systems. Our graduates will be future leaders in industry and academia world-wide, driving development of the ORE sector, helping to deliver the Government's carbon reduction targets for 2050 and ensuring that the UK remains at the forefront of this vitally important sector. In order to prepare students for the sector in which they will work, CDT-WAMSS will look to the future and focus on areas that will be relevant from 2023 onwards, which are not necessarily the issues of the past and present. For this reason, the scope of CDT-WAMSS will, in addition to in-stilling a solid understanding of wind and marine energy technologies and engineering, have a particular emphasis on: safety and safe systems, emerging advanced power and control technologies, floating substructures, novel foundation and anchoring systems, materials and structural integrity, remote monitoring and inspection including autonomous intervention, all within a cost competitive and environmentally sensitive context. The proposed new EPSRC CDT in Wind and Marine Energy Systems and Structures will provide an unrivalled Offshore Renewable Energy training environment supporting 70 students over five cohorts on a four-year doctorate, with a critical mass of over 100 academic supervisors of internationally recognised research excellence in ORE. The distinct and flexible cohort approach to training, with professional engineering peer-to-peer learning both within and across cohorts, will provide students with opportunities to benefit from such support throughout their doctorate, not just in the first year. An exceptionally strong industrial participation through funding a large number of studentships and provision of advice and contributions to the training programme will ensure that the training and research is relevant and will have a direct impact on the delivery of the UK's carbon reduction targets, allowing the country to retain its world-leading position in this enormously exciting and important sector.
Imagine a future where autonomous systems are widely available to improve our lives. In this future, autonomous robots unobtrusively maintain the infrastructure of our cities, and support people in living fulfilled independent lives. In this future, autonomous software reliably diagnoses disease at early stages, and dependably manages our road traffic to maximise flow and minimise environmental impact. Before this vision becomes reality, several major limitations of current autonomous systems need to be addressed. Key among these limitations is their reduced resilience: today's autonomous systems cannot avoid, withstand, recover from, adapt, and evolve to handle the uncertainty, change, faults, failure, adversity, and other disruptions present in such applications. Recent and forthcoming technological advances will provide autonomous systems with many of the sensors, actuators and other functional building blocks required to achieve the desired resilience levels, but this is not enough. To be resilient and trustworthy in these important applications, future autonomous systems will also need to use these building blocks effectively, so that they achieve complex technical requirements without violating our social, legal, ethical, empathy and cultural (SLEEC) rules and norms. Additionally, they will need to provide us with compelling evidence that the decisions and actions supporting their resilience satisfy both technical and SLEEC-compliance goals. To address these challenging needs, our project will develop a comprehensive toolbox of mathematically based notations and models, SLEEC-compliant resilience-enhancing methods, and systematic approaches for developing, deploying, optimising, and assuring highly resilient autonomous systems and systems of systems. To this end, we will capture the multidisciplinary nature of the social and technical aspects of the environment in which autonomous systems operate - and of the systems themselves - via mathematical models. For that, we have a team of Computer Scientists, Engineers, Psychologists, Philosophers, Lawyers, and Mathematicians, with an extensive track record of delivering research in all areas of the project. Working with such a mathematical model, autonomous systems will determine which resilience- enhancing actions are feasible, meet technical requirements, and are compliant with the relevant SLEEC rules and norms. Like humans, our autonomous systems will be able to reduce uncertainty, and to predict, detect and respond to change, faults, failures and adversity, proactively and efficiently. Like humans, if needed, our autonomous systems will share knowledge and services with humans and other autonomous agents. Like humans, if needed, our autonomous systems will cooperate with one another and with humans, and will proactively seek assistance from experts. Our work will deliver a step change in developing resilient autonomous systems and systems of systems. Developers will have notations and guidance to specify the socio-technical norms and rules applicable to the operational context of their autonomous systems, and techniques to design resilient autonomous systems that are trustworthy and compliant with these norms and rules. Additionally, developers will have guidance to build autonomous systems that can tolerate disruption, making the system usable in a larger set of circumstances. Finally, they will have techniques to develop resilient autonomous systems that can share information and services with peer systems and humans, and methods for providing evidence of the resilience of their systems. In such a context, autonomous systems and systems of systems will be highly resilient and trustworthy.
Technology companies, such as Google, Meta and Apple (Big Tech) are among the most influential actors in the modern world. Despite affecting the lives of millions of people, they operate with minimal regulatory framework. Their economic, social and political role is significant, and yet, governments across the world are uncertain about how to regulate them. Currently, the most discussed tools for regulation are competition and media laws, privacy laws, and the development of new sector-specific regulations. While such regulations are essential, the policy focuses on public law, disregarding the potential of private law tools. This project aims to remedy this and analyze how corporate governance could be used as a regulatory tool to regulate Big Tech's management behaviour and decisions.What? Why? How?