Supervisors: Istvan Cziegler (lead University of York), Christopher Ridgers (University of York) & Kevin Verhaegh (lead CCFE).
One of the foremost challenges of magnetic fusion energy is allowing efficient power exhaust while maintaining core performance. Conventional divertor devices currently struggle with this, prompting exploration of alternative divertor concepts (ADCs). Among these, the MAST Upgrade Super-X divertor (SXD) shows promise with its substantial reductions in target heat loading and enhanced plasma detachment access, in agreement with predictive simulations. To comprehend divertor exhaust and validate plasma-edge simulations for reactor extrapolation, innovative diagnostics and analysis techniques are essential. Recent advancements on MAST-U and other devices have greatly accelerated diagnostic and data analysis technique development, accelerating the understanding of plasma detachment through the use of innovative imaging diagnostics and developing integrated data analysis (IDA) techniques to exploit them. These are pivotal to MAST-U’s exhaust research.
Such in-depth studies in the divertor have been focussed on the steady-state processes of the plasmas (~10+ ms). This project addresses key knowledge gaps in fusion energy research by probing fast transients in the divertor plasma, studying the burn-through of edge localised modes (ELMs) and MHD perturbations (0.1-2 ms) through the detached region, which can cause melting in a reactor, as well as the impact of divertor turbulence and filaments (0.01-0.1 ms).
Leveraging integrated data analysis techniques and specialised divertor diagnostics you will:
1. Investigate ELM burn-through in a detached divertor as a function of divertor topology, level of detachment, divertor fueling and seeding.
a. Compare results with heat flux measurements
b. Compare results against interpretive simulations. For this purpose, you will develop synthetic diagnostics.
2. Uncover the nature of divertor filaments, evaluating their perturbation on plasma parameters and their role in driving steady-state divertor conditions.
With these insights, you will empower more accurate predictions for reactors and contribute to demonstrating the viability of ADC based reactors. By delving into novel divertor concepts, scrape-off layer transport, and core-SOL-divertor relationships, you contribute to cutting-edge research.
The successful student will be trained to operate divertor diagnostics, interpret their output, set up simulations for the region of interest and techniques in the development of synthetic diagnostics for optical diagnostics. Integrated analysis will enhance broader analytical skills for science and engineering. Working in a large complex team such as required in a tokamak experiment will develop crucial communication and planning skills. Dissemination of work both at UKAEA and publicly is expected, supported and will strengthen presentation and scientific writing skills.
This experimental project will be based at UKAEA and will involve experiments, data analysis and potentially hands-on diagnostic work.
The project will be mainly based in Culham, Oxfordshire, but there is opportunity for travel to conferences and the possibility of collaboration with TCV, Lausanne.
This project is offered by University of York. For further information please contact Istvan Cziegler (istvan.cziegler@york.ac.uk).