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Particle transport constraints via Bayesian spectral fitting of multiple atomic lines

Dataset ·
DOI:https://doi.org/10.7910/DVN/0DG1IM· OSTI ID:1887868

Optimized operation of fusion devices demands detailed understanding of plasma transport, a problem that must be addressed with advances in both measurement and data analysis techniques. In this work, we adopt Bayesian inference methods to determine experimental particle transport, leveraging opportunities from high-resolution He-like ion spectra in a tokamak plasma. The Bayesian spectral fitting code is used to analyze resonance (w), forbidden (z), intercombination (x, y), and satellite (k, j) lines of He-like Ca following laser blow-off injections on Alcator C-Mod. This offers powerful transport constraints since these lines depend differently on electron temperature and density, but also differ in their relation to Li-like, He-like, and H-like ion densities, often the dominant Ca charge states over most of the C-Mod plasma radius. Using synthetic diagnostics based on the AURORA package, we demonstrate improved effectiveness of impurity transport inferences when spectroscopic data from a progressively larger number of lines are included.

Research Organization:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Plasma Science and Fusion Center
Sponsoring Organization:
USDOE Office of Science (SC), Fusion Energy Sciences (FES)
DOE Contract Number:
SC0014264
OSTI ID:
1887868
Country of Publication:
United States
Language:
English

Cited By (1)

Particle transport constraints via Bayesian spectral fitting of multiple atomic lines journal May 2021

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