A new algorithm to track fast ions in fusion reactors

Fusion reactors could some day provide a clean and nearly inexhaustible source of energy, but their development has proven to be challenging. Nevertheless, great progress has been made in recent decades and fusion research is now at a critical stage: ITER, the first test reactor anticipated to generate a surplus of energy, is being built and operation is planned to start around 2025. It will serve as a testbed for DEMO, a prototype for a commercially viable fusion power plant to be completed by 2050. The Culham Centre for Fusion Energy (CCFE) is a key contributor to this development: it operates the Joint European Torus (JET) which is currently the world's largest fusion test reactor. JET is important for experimental results and validation of simulation software, both of which are used to inform the design of the much larger ITER

Computer simulations complementing experiments with test reactors are critical for the design and operation of ITER but also to explore alternative reactor designs. The immense complexity of the physics involved translates into complex mathematical models which take a long time to solve numerically, even on modern computer architectures. As reactors grow in size and complexity, so do the employed models and therefore solution times. LOCUST, for example, is a state-of-the-art particle tracker used operationally at CCFE and optimised heavily to exploit graphical processing unit (GPU) accelerators. However, one simulation of the trajectories of fast ions generated from neutral beam injection in the JET test reactor still takes around 10 hours to complete. Because of the higher energies, a similar simulation for ITER already takes 4 to 7 days. Therefore, at the moment, design choices can be informed only by a small number of simulations with carefully selected parameters. However, systematic exploration of a wide range of design parameters in computer simulations is not yet possible.

The project will develop a new and more efficient algorithm and deploy it as a particle tracker in CCFE's operational simulation software. This will help to significantly reduce solution times and contribute toward the order of magnitude reduction of runtimes needed for effective in-silico design of components for ITER. While the new algorithm will be deployed for a specific application, the mathematical ideas developed during the project can help to improve the efficiency of computer simulations in other applications such as manufacturing processes involving plasmas, for example for flat panel displays or solar panels.

The new, more efficient algorithm to be developed in the project has a wide range of potential applications within academia and industry. The immediate beneficiaries will be researchers at Culham Centre for Fusion Energy who use the simulation framework in which the method will be deployed to design and operate fusion reactors. After the project, other fusion research institutes can adopt the new algorithm as well.

Even though fusion energy is still largely an academic endeavour, some potential economic beneficiaries can be identified and the project will support the PI in building a corresponding network. For example, a handful of companies in the UK and US exploring alternative pathways to commercial fusion have formed in recent years (e.g. Helion Energy). Just as governmental research centres, these start-ups could benefit from more efficient numerical algorithms and modelling software. There also exist a small number of companies in the UK and abroad selling commercial simulation software (e.g. Tech-X, Mathworks, COMSOL). Integrating the new algorithm into their codes would increase the attractiveness of their product and help them to stay competitive.

In two or three decades, when fusion reactors become a commercially viable source of energy, companies serving this market will most certainly use computer simulations to support efficient and safe reactor operation. The mathematical ideas from the project could still be useful to help making the very advanced modelling software likely to exist at this stage efficient. Wide dissemination of results to both academic and industrial stakeholders in the field of fusion research will maximise the chance of them being used and developed further.

Plasmas and, as a corollary, computer simulations of plasmas, have become an important part in some industrial processes. Low temperature plasmas (LTPs), for example, underpin a range of important applications: they are used for the production of e.g. flat panel displays, solar panels or semiconductor chips. Very recently, ideas have been formulated how low temperature plasmas could aid scaling up the production of graphene. Even cancer treatment is being studied as a potential application. Computer modelling plays an important role in development and optimisation of LTP-based production processes, because simulations are typically much cheaper than experiments. Reducing solution times improves productivity and helps to save costs by shortening the design process. A widely used type of model are particle-in-cell codes, used e.g. in commercial codes like VSim by Tech-X or Starfish by Particle in Cell Consulting LLC. Adopting the ideas from the project for commercial codes would allow a large range of possible applications to benefit from the increase in efficiency from the new algorithm. University of York has an excellent research group in low temperature plasma and the PI will establish contacts during the project to communicate results and to explore potential industrial applications.

Nuclear fusion recreates physical processes on earth normally only found in stars: it is an exciting topic that can attract interest from laymen and the general public. Research during the project makes for good material to be presented during Open Days or similar outreach events organised at the host. These events target sixth-form students and presenting results from an exciting topic like fusion could illustrate the importance of acquiring mathematical skills, motivating them to pursue a career in engineering and, on the longer run, contribute to bringing more STEM educated people into the workforce.

Lastly, the project will contribute to the training of a PDRA in computational mathematics and fusion reactor modelling. It will also open up a new important application for the PI's research, contribute to his teaching and help to extend his scientific network.