This project is open to Honours, Master and or PhD students and can be scaled accordingly.

Fusion plasmas can support a wide range of electromagnetic waves, ranging from pressure and current gradient driven modes to those driven unstable by fast particle-wave resonance. In a tokamak such magnetohydrodynamic (MHD) modes vary in impact on the plasma, and range from performance limitation (edge localised modes) through to disruption (edge current driven kink). The diagnosis and control of fusion plasmas is contingent on the accurate modelling, prediction, and reliable measurement of such modes.

The ITER tokamak is the world’s largest science project. When constructed in 2025 it will be the world’s largest and highest performance tokamak, designed to demonstrate the scientific feasibility of fusion power. An opportunity exists to work with scientists in the ITER Organisation to develop an integrated modelling solution for the statistical inference of MHD/EP driven mode activity, initially focusing on magnetic probes data. The components include:

(a) Synthetic data generation: use of MHD/energetic particle codes to generate synthetic diagnostic data convolved with noise.

(b) MHD analysis: develop and install analysis tools to extract mode numbers, wave vector, polarization, and compute mode statistics.

(c) Statistical inference: develop a Bayesian inference implementation of (b).

The plasma Theory and Modelling Group has extensive expertise in the computation of equilibrium and stability in toroidal confinement (both tokamaks and stellarators). Prof. Hole, an ITER Science Fellow, is an international expert in MHD analysis of fusion plasmas, spanning probe design and construction, through to advanced signal processing and MHD analysis. The project would also extend existing expertise in the Bayesian inference of tokamak equilibria to mode analysis. The project also has clear scope to expand to other diagnostics.

In general, the integrated modelling of complex systems with a large collection of heterogeneous diagnostics with physics/process models is an outstanding modelling challenge portable to other fields, such as climate science.