The United Kingdom and Japan have reportedly entered into a research and technology deployment agreement for supporting the automation of numerous aspects of fusion energy production and nuclear decommissioning. This globally-leading alliance is slated to witness the application of new automation and robotics techniques for the decommissioning of nuclear facilities as well as fusion research in Japan and the United Kingdom.
According to Amanda Solloway, UK’s Minister of Science, Research, and Innovation, it is vital that the United Kingdom works in collaboration with international partners for unlocking the amazing potential of nuclear power. This would enable the safe decommission of nuclear sites, in turn supporting the evolving research initiatives in the area of fusion, plausibly offer an unlimited source of clean energy.
The Minister has further elaborated that this innovative research alliance with Japan will make sure that UK’s expertise in robotics is capable of combating complex challenges including nuclear decommissioning, helping to secure highly skilled jobs as the nation builds back better from the coronavirus pandemic.
As per sources, the UK-Japanese robotics project, the “LongOps”, which amounts to £12M, will support the delivery of safer and faster decommissioning at TEPCO’s Fukushima Dai-chi reactors in Japan and at Sellafield in the United Kingdom.
Furthermore, the four-year research agreement will be financed equally by Japan’s Tokyo Electric Power Company (“TEPCO”), the UK Research and Innovation (“UKRI”), and the UK’s Nuclear Decommissioning Authority. The agreement is also set to witness UKAEA’s “RACE” (Remote Applications in Challenging Environments) facility lead the project and design strategy, while delivering new robotic capacities having global capacity.
Additionally, the LongOps initiative will also be equipped to deploy revolutionary digital twin technology, comprising virtual models where the pairing of the physical and virtual worlds would allow for a highly detailed analysis of data, along with the estimation of potential operational and maintenance issues.