54 citations · 349 across the 18 of their papers we have counts for
18 papers
Machine-Learning enabled analysis of ELM filament dynamics in KSTAR
Cooper Jacobus, Minjun J. Choi, Ralph Kube
The emergence and dynamics of filamentary structures associated with edge-localized modes (ELMs) inside tokamak plasmas during high-confinement mode is regularly studied using Elec…
Machine learning accelerated particle-in-cell plasma simulations
R. Kube, R. M. Churchill, B. Sturdevant
Particle-In-Cell (PIC) methods are frequently used for kinetic, high-fidelity simulations of plasmas. Implicit formulations of PIC algorithms feature strong conservation properties…
Near real-time streaming analysis of big fusion data
Ralph Kube, R. Michael Churchill, CS Chang +6
While experiments on fusion plasmas produce high-dimensional data time series with ever increasing magnitude and velocity, data analysis has been lagging behind this development. F…
Comparison between mirror Langmuir probe and gas puff imaging measurements of intermittent fluctuations in the Alcator C-Mod scrape-off layer
R. Kube, A. Theodorsen, O. E. Garcia +3
Statistical properties of the scrape-off layer (SOL) plasma fluctuations are studied in ohmically heated plasmas in the Alcator C-Mod tokamak. For the first time, plasma fluctuatio…
Non-Oberbeck-Boussinesq zonal flow generation
Markus Held, Matthias Wiesenberger, Ralph Kube +1
Novel mechanisms for zonal flow (ZF) generation for both large relative density fluctuations and background density gradients are presented. In this non-Oberbeck-Boussinesq (NOB) r…
Outlier classification using Autoencoders: application for fluctuation driven flows in fusion plasmas
R. Kube, F. M. Bianchi, D. Brunner +1
Understanding the statistics of fluctuation driven flows in the boundary layer of magnetically confined plasmas is desired to accurately model the lifetime of the vacuum vessel com…