10 citations · 12 across the 4 of their papers we have counts for
6 papers · 1 filter
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…
Emulation Techniques for Scenario and Classical Control Design of Tokamak Plasmas
A. Agnello, N. C. Amorisco, A. Keats +5
The optimisation of scenarios and design of real-time-control in tokamaks, especially for machines still in design phase, requires a comprehensive exploration of solutions to the G…
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…