39 citations · 91 across the 19 of their papers we have counts for
9 papers · 1 filter
Bayesian optimisation of poloidal field coil positions in tokamaks
Timothy Nunn, Kamran Pentland, Vignesh Gopakumar +1
The tokamak is a world-leading concept for producing sustainable energy via magnetically-confined nuclear fusion. Identifying where to position the magnets within a tokamak, specif…
Neural operator surrogate models of plasma edge simulations: feasibility and data efficiency
N. Carey, L. Zanisi, S. Pamela +7
The inclusion of high-fidelity simulations of SOL turbulence and transient MHD events such as ELMs in highly iterative applications remains computationally prohibitive, limiting th…
Neural-Parareal: Dynamically Training Neural Operators as Coarse Solvers for Time-Parallelisation of Fusion MHD Simulations
S. J. P. Pamela, N. Carey, J. Brandstetter +10
The fusion research facility ITER is currently being assembled to demonstrate that fusion can be used for industrial energy production, while several other programmes across the wo…
Data efficiency and long term prediction capabilities for neural operator surrogate models of core and edge plasma codes
N. Carey, L. Zanisi, S. Pamela +4
Simulation-based plasma scenario development, optimization and control are crucial elements towards the successful deployment of next-generation experimental tokamaks and Fusion po…
Plasma Surrogate Modelling using Fourier Neural Operators
Vignesh Gopakumar, Stanislas Pamela, Lorenzo Zanisi +10
Predicting plasma evolution within a Tokamak reactor is crucial to realizing the goal of sustainable fusion. Capabilities in forecasting the spatio-temporal evolution of plasma rap…
Efficient training sets for surrogate models of tokamak turbulence with Active Deep Ensembles
L. Zanisi, A. Ho, T. Madula +7
Model-based plasma scenario development lies at the heart of the design and operation of future fusion powerplants. Including turbulent transport in integrated models is essential…
Shaping of Magnetic Field Coils in Fusion Reactors using Bayesian Optimisation
Timothy Nunn, Vignesh Gopakumar, Sebastien Kahn
Nuclear fusion using magnetic confinement holds promise as a viable method for sustainable energy. However, most fusion devices have been experimental and as we move towards energy…
Multi-objective Bayesian optimization for design of Pareto-optimal current drive profiles in STEP
Theodore Brown, Stephen Marsden, Vignesh Gopakumar +3
The safety factor profile is a key property in determining the stability of tokamak plasmas. To design the safety factor profile in the United Kingdom's proposed Spherical Tokamak…
Fourier Neural Operator for Plasma Modelling
Vignesh Gopakumar, Stanislas Pamela, Lorenzo Zanisi +3
Predicting plasma evolution within a Tokamak is crucial to building a sustainable fusion reactor. Whether in the simulation space or within the experimental domain, the capability…