Real‐time estimation of the electron temperature profile in  DIII‐D by leveraging neural‐network surrogate models

Single Gaussian Process Method for Arbitrary Tokamak Regimes with a Statistical Analysis

(2022) Jarrod Leddy et al.   PLASMA PHYSICS AND CONTROLLED FUSION

Neural network model of the Multi-Mode Anomalous Transport Module for accelerated transport simulations

(2021) Shira Morosohk et al.   NUCLEAR FUSION

Model-based electron density profile estimation and control, applied to ITER

(2021) T O S J Bosman et al.   Journal of Physics Communications

Accelerated version of NUBEAM capabilities in DIII-D using neural networks

(2020) Shira M. Morosohk et al.   FUSION ENGINEERING AND DESIGN

CAKE: Consistent Automatic Kinetic Equilibrium reconstruction

(2020) Z.A. Xing et al.   FUSION ENGINEERING AND DESIGN

Real-time capable modeling of neutral beam injection on NSTX-U using neural networks

(2019) M.D. Boyer et al.   NUCLEAR FUSION

Control-oriented modeling of the plasma particle density in tokamaks and application to real-time density profile reconstruction

(2018) T.C. Blanken et al.   FUSION ENGINEERING AND DESIGN

OMFIT Tokamak Profile Data Fitting and Physics Analysis

(2018) N. C. Logan et al.   FUSION SCIENCE AND TECHNOLOGY

Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

(2018) F. Felici et al.   NUCLEAR FUSION

Self-consistent core-pedestal transport simulations with neural network accelerated models

(2017) O. Meneghini et al.   NUCLEAR FUSION

Real-time capable first principle based modelling of tokamak turbulent transport

(2015) J. Citrin et al.   NUCLEAR FUSION

Physics basis of Multi-Mode anomalous transport module

(2013) T. Rafiq et al.   PHYSICS OF PLASMAS