Nuclear fusion is an environmentally friendly source of energy that produces no CO2 or other harmful emissions, and therefore does not lead to global warming. This exciting PhD project will contribute to the ongoing research effort to make the technology viable by developing solutions for the effective use of multi-robot systems for the inspection of nuclear fusion infrastructure.
The operation of a fusion reactor like the planned European DEMOnstration power plant (DEMO - https://www.euro-fusion.org/programme/demo/
) will require the use of remotely-operated robotic systems in challenging inspection and maintenance procedures. These procedures must be carried out in a timely and reliable manner, and in a confined and harsh environment. The PhD project will investigate ways in which Common Cause Failure (CCF) vectors associated with maintenance and inspection robotic systems can arise, the effects of these vectors and how to provide assurance that as a result the (safety) risk associated with maintenance action using robots can be minimised.
CCFs arise as a result of dependencies between multiple elements of a system. An initiating event leads through one or more coupling factors to a failure of multiple components and sub-systems. Possible coupling factors can be introduced throughout the lifecycle and include
• Organisation - Same group of “actors” responsible for activities that should be independent.
• Maintenance - Same “actor” maintains supposedly independent equipment.
• Data Sources - Independent equipment relies on information through same channel
• Design - Physically redundant components have same systematic fault.
• Physical Proximity of Equipment – Event removes multiple layers of “independent” protection
• Common Vulnerability - Similar technologies with unanticipated weakness, e.g. software operating systems, data security, environmental factors such as Electromagnetic Interference
Potential effects of these CCFs on autonomous robotic systems and the Fusion Reactors:
• Reduced capability of the reactors
• Unreliability / Unavailability of robotic equipment
• Increased inspection and maintenance of robotic equipment and the reactor
• Poor understanding of plant state and therefore plant robustness and resilience
• Undermining of Safety characteristics and safety case
You will be working alongside Phd and post-doctoral researchers working on related subjects and will thus form part of a vibrant research community.
The project is jointly funded by the UK Atomic Energy Authority’s Remote Applications in Challenging Environments programme (http://www.race.ukaea.uk/
), by the York-led Assuring Autonomy International Programme (https://www.york.ac.uk/assuring-autonomy/
), and by the University of York’s Department of Computer Science.
The successful candidate will conduct your research under the supervision of Dr Mark Nicholson https://www.cs.york.ac.uk/people/mark
) and Prof John McDermid (https://www.cs.york.ac.uk/people/jam
Apply for this studentship
1. Apply to study
• You must apply online for a full-time PhD in Computer Science (https://www.cs.york.ac.uk/postgraduate/research-degrees/phd/#tab-4
• You must quote the project title (Common Cause Vectors in Robotic Autonomous Systems for Fusion Reactors) in your application.
• There is no need to write a full formal research proposal (2,000-3,000 words) in your application to study as this studentship is for a specific project.
2. Provide a personal statement. As part of your application please provide a personal statement of 500-1,000 words with your initial thoughts on the research topic.
The closing date for the receipt of applications is 31 January 2020.
Interviews are expected to take place within approximately 14 days of the closing date.
The studentship will begin in October 2020.
Dr. Mark Nicholson : [email protected]
1. PETER – Pan-European Training, Research and Education Network On Electromagnetc Risk
Management, iiw.kuleuven.be/onderzoek/peter (3 places are at York)
2. Assuring Autonomy International Programme, www.york.ac.uk/assuring-autonomy/
3. RIMA - https://rimanetwork.eu
4. RACE - www.race.ukaea.uk
5. IAEA, “Protecting against Common Cause Failures in Digital I&C Systems of Nuclear Power Plants
6. Marshall, F. M., A. Mosleh, and D. M. Rasmuson. "Common-Cause Failure Database and Analysis
System: Event Definition and Classification, NUREG/CR-6268 (INEEL/EXT-97-00696)." (1998).
7. Le Duy, Tu Duong, and Dominique Vasseur. "A practical methodology for modeling and
estimation of Common Cause Failure Parameters in multi-unit nuclear PSA model." Reliability
Engineering & System Safety 170 (2018): 159-174.
8. Leonardi, Fabio, Fabrizio Messina, and Corrado Santoro. "A Risk-Based Approach to Automate
Preventive Maintenance Tasks Generation by Exploiting Autonomous Robot Inspections in Wind
Farms." IEEE Access 7 (2019): 49568-49579.