9 citations · 19 across the 12 of their papers we have counts for
12 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: integration and testing in the MAST-U PCS
Matthew J. Marshall, Edward Jones, Graham J. McArdle +10
The deployment of advanced, AI-enabled control algorithms in tokamak experiments requires robust integration with existing plasma control system (PCS) architectures and extensive p…
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…
Real-Time Applicability of Emulated Virtual Circuits for Tokamak Plasma Shape Control
Pedro Cavestany, Alasdair Ross, Adriano Agnello +5
Machine learning has recently been adopted to emulate sensitivity matrices for real-time magnetic control of tokamak plasmas. However, these approaches would benefit from a quantif…
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…
Multiple solutions to the static forward free-boundary Grad-Shafranov problem on MAST-U
K. Pentland, N. C. Amorisco, P. E. Farrell +1
The Grad-Shafranov (GS) equation is a nonlinear elliptic partial differential equation that governs the ideal magnetohydrodynamic equilibrium of a tokamak plasma. Previous studies…
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…
Error bound analysis of the stochastic parareal algorithm
Kamran Pentland, Massimiliano Tamborrino, T. J. Sullivan
Stochastic parareal (SParareal) is a probabilistic variant of the popular parallel-in-time algorithm known as parareal. Similarly to parareal, it combines fine- and coarse-grained…
GParareal: A time-parallel ODE solver using Gaussian process emulation
Kamran Pentland, Massimiliano Tamborrino, T. J. Sullivan +2
Sequential numerical methods for integrating initial value problems (IVPs) can be prohibitively expensive when high numerical accuracy is required over the entire interval of integ…
Stochastic parareal: an application of probabilistic methods to time-parallelisation
Kamran Pentland, Massimiliano Tamborrino, D. Samaddar +1
Parareal is a well-studied algorithm for numerically integrating systems of time-dependent differential equations by parallelising the temporal domain. Given approximate initial va…