Details of Grant 

EPSRC Reference:	EP/W001128/1
Title:	Robotics and Artificial Intelligence for Nuclear Plus (RAIN+)
Principal Investigator:	Lennox, Professor B
Other Investigators:	Martin, Dr PG Maple, Professor C Arvin, Dr F Wright, Professor NG Harwin, Professor W Carrasco, Dr J Hawes, Professor N Dennis, Dr L Watson, Dr SA Weightman, Dr A Boyle, Dr JH Buckingham, Dr R Havoutis, Dr I Herrmann, Professor G Mohammad, Dr A Epiphaniou, Dr G Dixon, Professor C Scarfe, Dr P Benson, Dr S Tzemanaki, Dr A Adams, Mr RJ Scott, Professor TB Axinte, Professor DA Joyce, Professor MJ Fallon, Dr M Haroutunian, Dr M Dong, Dr X Richardson, Professor TS
Researcher Co-Investigators:
Project Partners:
Department:	Electrical and Electronic Engineering
Organisation:	University of Manchester, The
Scheme:	Standard Research
Starts:	01 April 2021	Ends:	31 March 2022	Value (£):	1,910,650
EPSRC Research Topic Classifications:	Human-Computer Interactions Instrumentation Eng. & Dev. Robotics & Autonomy
EPSRC Industrial Sector Classifications:	Energy
Related Grants:
Panel History:	Panel Date Panel Name Outcome 10 Dec 2020 ISCF RAI Hubs Interview 2020 Announced
Summary on Grant Application Form
The nuclear industry has a vast array of highly complex and diverse challenges that span decommissioning, waste management, fission power plants, advanced modular reactors and fusion reactors. In the UK, one of the most significant challenges is to decommission legacy storage facilities. There is estimated to be approximately 3,000 tonnes of high-level waste (HLW), 310,000 tonnes of intermediate level waste (ILW) and hundreds of radioactive facilities that need to be decommissioned in the UK alone. Despite significant progress during the first phase of RAIN, decommissioning continues to rely almost exclusively on manual operations, requiring people to enter extremely hazardous environments placing themselves at risk. Significant amounts of personal protective equipment (PPE) is required, which reduces dexterity and lowers productivity to levels significantly below that of other industries. PPE also adds significantly to the waste materials that must be disposed of and as a consequence, makes some future operations infeasible. For example, it has been estimated that more than 1 million suited entries will be required to decommission the THORP plant alone on the Sellafield site. RAI technologies are therefore considered essential if the UK is to address its decommissioning challenges. In the future generation of nuclear power, fusion reactors will not be able to operate without advances being made to remote handling equipment. In addition, remote inspection and maintenance of new fission reactors is essential if they are to be commercially viable. RAIN+ will continue to push the boundaries of Robotics and AI (RAI) science, developing robotic solutions that solve major challenges facing the nuclear sector. To ensure that the work is relevant, has a long-term impact on industry, and leads to deployments of RAI technology into active facilities, RAIN will continue to work in close partnership with nuclear end-users, the supply chain and regulators. Furthermore, recognising that many of the hazards encountered in the nuclear industry are prevalent in other industry sectors, such as agriculture, construction, offshore and healthcare, RAIN will work to expand its user and application base such that RAI solutions can be developed that have cross-sector relevance and a single hub for all challenging environments, not just nuclear, can be established towards the end of this second phase.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Further Information:
Organisation Website:	http://www.man.ac.uk