1 citations · 1 across the 1 of their papers we have counts for
7 papers
Kinetic Equilibrium Prediction at TCV using RAPTOR and FBT
C. E. Contré, A. Merle, O. Sauter +13
We present results from a new Kinetic-Equilibrium Prediction (KEP) workflow and shot preparation for full TCV discharges, by coupling predict-first RAPTOR transport simulations wit…
Technical Aspects of Plasma Operational Simulation (POPSIM): A Framework for Data-Driven Simulation and Control
Allen M. Wang, Zander Keith, Mark Dan Boyer +4
This paper reports on technical aspects of Plasma Operational Simulation (POPSIM), a research framework for data-driven simulation and control built in the machine learning framewo…
Learning Plasma Dynamics and Robust Rampdown Trajectories with Predict-First Experiments at TCV
Allen M. Wang, Alessandro Pau, Cristina Rea +12
The rampdown phase of a tokamak pulse is difficult to simulate and often exacerbates multiple plasma instabilities. To reduce the risk of disrupting operations, we leverage advance…
Correlation of the L-mode density limit with edge collisionality
Andrew Maris, Cristina Rea, Alessandro Pau +10
The "density limit" is one of the fundamental bounds on tokamak operating space, and is commonly estimated via the empirical Greenwald scaling. This limit has garnered renewed inte…
Plasma State Monitoring and Disruption Characterization using Multimodal VAEs
Yoeri Poels, Alessandro Pau, Christian Donner +6
When a plasma disrupts in a tokamak, significant heat and electromagnetic loads are deposited onto the surrounding device components. These forces scale with plasma current and mag…
Robust Confinement State Classification with Uncertainty Quantification through Ensembled Data-Driven Methods
Yoeri Poels, Cristina Venturini, Alessandro Pau +4
Maximizing fusion performance in tokamaks relies on high energy confinement, often achieved through distinct operating regimes. The automated labeling of these confinement states i…