6 papers
Real-time virtual circuits for plasma shape control via neural network emulators: experimental demonstration on MAST Upgrade
Nicola C. Amorisco, Kamran Pentland, Adriano Agnello +12
Conventional plasma shape control in tokamaks relies on virtual circuits (VCs) that are computed offline from linearisations around a small, tailored number of reference equilibria…
Real-time virtual circuits for plasma shape control via neural network emulators
Alasdair Ross, George K. Holt, Kamran Pentland +7
Reliable position and shape control in tokamak plasmas requires accurate real-time regulation of several strongly coupled shape parameters. The control vectors that disentangle the…
Real-time virtual circuits for plasma shape control via neural network emulators: dynamic validation in closed-loop simulations
K. Pentland, A. Ross, N. C. Amorisco +5
Reliable confinement and stable performance of tokamak fusion plasmas require accurate real-time magnetic shape control. A promising route to reduced latency and increased flexibil…
The FreeGSNKE Pulse Design Tool (FPDT): a computational framework for evolutive plasma scenario and control design
K. Pentland, N. C. Amorisco, A. Ross +8
We present the FreeGSNKE Pulse Design Tool (FPDT), an open-source, Python-based computational framework that enables in silico testing and predictive design of tokamak plasma scena…
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…
Calibrated Physics-Informed Uncertainty Quantification
Vignesh Gopakumar, Ander Gray, Lorenzo Zanisi +5
Simulating complex physical systems is crucial for understanding and predicting phenomena across diverse fields, such as fluid dynamics and heat transfer, as well as plasma physics…