85 citations · 286 across the 20 of their papers we have counts for
10 papers · 1 filter
MGKDB: An IMAS-aligned multicode gyrokinetic simulation database for reproducible fusion turbulence modeling and data-driven analysis
Craig Michoski, David R. Hatch, Dongyang Kuang +14
Expensive fusion simulations are commonly preserved in code-specific formats that limit discovery, comparison, and reuse. We present the Multiscale GyroKinetic DataBase (MGKDB), an…
The Fusion Equilibrium Challenge: Inferring Magnetic Geometry Without Magnetic Diagnostics
Tapan Ganatma Nakkina, Matthew Waller, Craig Michoski +6
Next-generation fusion reactor devices such as SPARC, ARC, and CFETR will operate in extreme neutron environments that compromise the magnetic sensors traditionally used to reconst…
The Data Fusion Labeler (dFL): Challenges and Solutions to Data Harmonization, Labeling, and Provenance in Fusion Energy
Craig Michoski, Matthew Waller, Brian Sammuli +14
Fusion energy research increasingly depends on the ability to integrate heterogeneous, multimodal datasets from high-resolution diagnostics, control systems, and multiscale simulat…
Quantifying Resolution Limits in Pedestal Profile Measurements with Gaussian Process Regression
Norman M. Cao, David R. Hatch, Craig Michoski +4
Edge transport barriers (ETBs) in magnetically confined fusion plasmas, commonly known as pedestals, play a crucial role in achieving high confinement plasmas. However, their defin…
Automated Estimation of Plasma Temperature and Density from Emission Spectroscopy
Todd A. Oliver, Craig Michoski, Samuel Langendorf +1
This paper introduces a novel approach for automated estimation of plasma temperature and density using emission spectroscopy, integrating Bayesian inference with sophisticated phy…
2022 Review of Data-Driven Plasma Science
Rushil Anirudh, Rick Archibald, M. Salman Asif +60
Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data…