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Inference of flow shear from reciprocating plasma potential measurements by means of Gaussian process regression
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- T. Nishizawa
- Research Institute for Applied Mechanics, Kyushu University 1 , Kasuga 816-8580,
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- S. Tokuda
- Institute of Mathematics for Industry, Kyushu University, Fukuoka 4 , Fukuoka 816-8580,
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- P. Manz
- Research Center for Plasma Turbulence, Kyushu University 2 , Kasuga 816-8580,
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- G. Grenfell
- Max-Planck-Institut für Plasmaphysik 7 , Boltzmannstr. 2, 85748 Garching,
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- M. Sasaki
- College of Industrial Technology Nihon University 8 , Narashino 275-8575,
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- S. Inagaki
- Institute of Advanced Energy, Kyoto University 9 , Uji, Kyoto 611-0011,
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- Y. Kawachi
- Graduate School of Engineering, Nagoya University 10 , Furo-cho, Chikusa-ku, Nagoya 464-8603,
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- A. Fujisawa
- Research Institute for Applied Mechanics, Kyushu University 1 , Kasuga 816-8580,
Bibliographic Information
- Published
- 2025-03-01
- Resource Type
- journal article
- DOI
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- 10.1063/5.0254473
- Publisher
- AIP Publishing
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Description
<jats:p>Reliable estimation of equilibrium flow shear from reciprocating probe measurements is challenging since the quantity of interest corresponds to the second derivative of the observable plasma potential. In addition, a time series of the plasma potential obtained by plunging a probe is affected by both the probe head position and plasma fluctuations, complicating the estimation of equilibrium components and their errors. We tackle this problem by employing Gaussian process regression that is able to infer even the derivatives of a spatial or temporal profile in the form of a probability distribution function. The proposed inference framework is validated by using synthetic data generated by gyrofluid simulations. While the inference result based on a single plunge is unstable in certain spatial locations, we have obtained reasonable agreement between the inference result and the true flow shear profile by combining data sets taken from several plunges.</jats:p>
Journal
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- Physics of Plasmas
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Physics of Plasmas 32 (3), 2025-03-01
AIP Publishing
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Details 詳細情報について
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- CRID
- 1360306904389925504
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- ISSN
- 10897674
- 1070664X
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- Article Type
- journal article
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- Data Source
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- Crossref
- KAKEN
