23 citations · 44 across the 12 of their papers we have counts for
12 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…
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…
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…
Accelerating Simulation of Two-Phase Flows with Neural PDE Surrogates
Yoeri Poels, Koen Minartz, Harshit Bansal +1
Simulation is a powerful tool to better understand physical systems, but generally requires computationally expensive numerical methods. Downstream applications of such simulations…
On learning latent dynamics of the AUG plasma state
A. Kit, A. E. Järvinen, Y. R. J. Poels +5
In this work, we demonstrate the utility of state representation learning applied to modeling the time evolution of electron density and temperature profiles at ASDEX-Upgrade (AUG)…
Fast Dynamic 1D Simulation of Divertor Plasmas with Neural PDE Surrogates
Yoeri Poels, Gijs Derks, Egbert Westerhof +3
Managing divertor plasmas is crucial for operating reactor scale tokamak devices due to heat and particle flux constraints on the divertor target. Simulation is an important tool t…
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics
Koen Minartz, Yoeri Poels, Simon Koop +1
Neural networks are emerging as a tool for scalable data-driven simulation of high-dimensional dynamical systems, especially in settings where numerical methods are infeasible or c…
Towards Learned Simulators for Cell Migration
Koen Minartz, Yoeri Poels, Vlado Menkovski
Simulators driven by deep learning are gaining popularity as a tool for efficiently emulating accurate but expensive numerical simulators. Successful applications of such neural si…
Developing Deep Learning Algorithms for Inferring Upstream Separatrix Density at JET
A. Kit, A. Jaervinen, S. Wiesen +2
Predictive and real-time inference capability for the upstream separatrix electron density, , is essential for design and control of core-edge integrated plasma sc…
VAE-CE: Visual Contrastive Explanation using Disentangled VAEs
Yoeri Poels, Vlado Menkovski
The goal of a classification model is to assign the correct labels to data. In most cases, this data is not fully described by the given set of labels. Often a rich set of meaningf…
Overlap-free Drawing of Generalized Pythagoras Trees for Hierarchy Visualization
Tanja Munz, Michael Burch, Toon van Benthem +3
Generalized Pythagoras trees were developed for visualizing hierarchical data, producing organic, fractal-like representations. However, the drawback of the original layout algorit…