Supervisors: Suresh Perin (University of York)
The development of maintenance and through-life management of commercial fusion power plants present a unique set of challenges associated with the complexity of the systems. In the project, a digital twin model will be developed for through-life management of a “divertor”. The divertor sits at the bottom of the fusion plant and extracts heat and ash produced by the fusion reaction, minimises plasma contamination, and protects the surrounding walls from thermal and neutronic loads. Hence, it is subject to a very harsh environment with high-energy plasma particle strike and high heat flux. The heat flux sustained by the ITER divertor vertical targets is estimated at 10 MWm² at steady state and 20 MWm² at slow transients (https://www.iter.org/mach/Divertor). Furthermore, when issues arise with the fusion rector, i.e. plasma disruption events, the energy stored in the plasma falls on the divertor, and the heat load is estimated to be several hundred or several thousand times more than that in normal operation.
Hence, the development of reliability and through-life management for the divertor is one of the major challenges encountered in the realisation of a nuclear fusion power plant based on the tokamak concept. Furthermore, as these fusion technologies, such as the divertor, are in their early phase of development, operational data from these systems are not available and their fabrication processes are not well industrialised, unlike other complex systems, such as aircraft and space shuttles.
Hence, it is difficult to develop maintenance policies, in-service monitoring and plant inspections for through-life management of fusion power plant components considering different failure modes at the current developmental stage. This project attempts to develop a hybrid modelling strategy, with a series of interconnected multi-scale, multi-physics computational models combined with digital measurement data from available experimental data from the “divertor” to build a digital twin model of the “divertor” for exploring generic plant performance and developing maintenance policies and in-service monitoring of the fusion power plant.
A key aspect of the hybrid modelling approach will be quantitative validation of multi-physics and data-driven models and establishing credibility in failure predictions through physical testing and quantifying uncertainty. However, these approaches are difficult for the tokamak reactor as its sub-systems are not yet tested and validated in full operational conditions in a fusion reactor. A gap remains between current level testing undertaken and then using these tests to validate system-level models. Thus, new strategies and techniques will be considered in this project to close this gap in knowledge and improve the confidence levels of digital twin system-level models for in-service monitoring and prognostics predictions for predictive maintenance.
The University of York has considerable expertise in divertor design physics (https://www.york.ac.uk/physics-engineering-technology/ypi/research/mcf/divphys/). The multi-physics models developed at the University will be used for the digital twin development. Furthermore, collaboration with SPARC, a tokamak under development by Commonwealth Fusion Systems in collaboration with the Massachusetts Institute of Technology, will also be considered in the PhD to validate the digital twin models for the “divertor”. The SPARC is expected to operate around 2025 as a digital twin machine.
The supervisory/advisory team has competencies in multi-physics computational simulation, data-centric engineering, machine learning, digital twin development, prognostics health management and predictive maintenance. The potential student will learn from their engagement with the supervisors/advisors and acquire the above-mentioned skills. These will be very useful skills for future design, manufacturing, implementation and through-life management of future fusion energy plant. The student will be also encouraged to attend soft skills and professional development courses, such as those related to presentation, communication, scientific writing, analytical skills, etc.
The project will be mainly based at University of York with some travel to CCFE and international conferences.
This project is offered by University of York. For further information please contact: email@example.com
Li, L., Aslam, S., Wileman, A. and Perinpanayagam, S. (2021) ‘Digital Twin in Aerospace Industry: A Gentle Introduction’, IEEE Access, https://ieeexplore.ieee.org/document/9656111