Inference of experimental radial impurity transport on Alcator C-Mod: Bayesian parameter estimation and model selection
Name
2006.06798.pdf
Description
Submitted version
Size
1.95 MB
Format
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Checksum (MD5)
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Author(s)
Sciortino, F
Howard, NT
Marmar, ES
Odstrcil, T
Cao, NM
Dux, R
Hubbard, AE
Hughes, JW
Irby, JH
Marzouk, YM
Date Issued
2020
Journal
Nuclear Fusion
Publisher
IOP Publishing
Version
Original manuscript
Abstract
© 2020 IAEA, Vienna We present a fully Bayesian approach for the inference of radial profiles of impurity transport coefficients and compare its results to neoclassical, gyrofluid and gyrokinetic modeling. Using nested sampling, the Bayesian impurity transport inference (BITE) framework can handle complex parameter spaces with multiple possible solutions, offering great advantages in interpretative power and reliability with respect to previously demonstrated methods. BITE employs a forward model based on the pySTRAHL package, built on the success of the well-known STRAHL code (Dux 2003 Fusion Sci Technol. 44 708-15), to simulate impurity transport in magnetically-confined plasmas. In this paper, we focus on calcium (Ca, Z = 20) laser blow-off injections into Alcator C-Mod plasmas. Multiple Ca atomic lines are diagnosed via high-resolution x-ray imaging crystal spectroscopy and vacuum ultra-violet measurements. We analyze a sawtoothing I-mode discharge for which neoclassical and turbulent (quasilinear and non-linear) predictions are also obtained. We find good agreement in diffusion across the entire radial extent, while turbulent convection and density profile peaking are estimated to be larger in experiment than suggested by theory. Efforts and challenges associated with the inference of experimental pedestal impurity transport are discussed.
MIT Department
Massachusetts Institute of Technology. Plasma Science and Fusion Center
Massachusetts Institute of Technology. Department of Physics
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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DOI of Published Version
https://doi.org/10.1088/1741-4326/ABAE85
