U.S. Department of EnergyOffice of Scientific and Technical Information
Particle transport constraints via Bayesian spectral fitting of multiple atomic lines
Abstract
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.
- Authors:
-
- OSTI
- Publication Date:
- DOE Contract Number:
- SC0014264
- Research Org.:
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Plasma Science and Fusion Center
- Sponsoring Org.:
- USDOE Office of Science (SC), Fusion Energy Sciences (FES)
- Subject:
- 70 PLASMA PHYSICS AND FUSION TECHNOLOGY
- OSTI Identifier:
- 1887868
- DOI:
- https://doi.org/10.7910/DVN/0DG1IM
Citation Formats
Sciortino, F., Cao, N. M., Howard, N. T., Marmar, E. S., and Rice, J. E. Particle transport constraints via Bayesian spectral fitting of multiple atomic lines. United States: N. p., 2021.
Web. doi:10.7910/DVN/0DG1IM.
Sciortino, F., Cao, N. M., Howard, N. T., Marmar, E. S., & Rice, J. E. Particle transport constraints via Bayesian spectral fitting of multiple atomic lines. United States. doi:https://doi.org/10.7910/DVN/0DG1IM
Sciortino, F., Cao, N. M., Howard, N. T., Marmar, E. S., and Rice, J. E. 2021.
"Particle transport constraints via Bayesian spectral fitting of multiple atomic lines". United States. doi:https://doi.org/10.7910/DVN/0DG1IM. https://www.osti.gov/servlets/purl/1887868. Pub date:Thu Jun 03 00:00:00 EDT 2021
@article{osti_1887868,
title = {Particle transport constraints via Bayesian spectral fitting of multiple atomic lines},
author = {Sciortino, F. and Cao, N. M. and Howard, N. T. and Marmar, E. S. and Rice, J. E.},
abstractNote = {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.},
doi = {10.7910/DVN/0DG1IM},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jun 03 00:00:00 EDT 2021},
month = {Thu Jun 03 00:00:00 EDT 2021}
}