Regularization of soft-X-ray data in a tokamak application
Abstract
An image inversion scheme for soft X-ray (SXR) diagnostics at the DIII-D tokamak is developed to obtain the local soft X-ray emission at a poloidal cross-section from the spatially line-integrated image taken by either a set of SXR arrays or a tangential camera. The scheme uses the Tikhonov regularization method since the inversion problem is generally ill-posed. The regularization technique uses the generalized singular value decomposition (GSVD) to determine a solution that depends on a free regularization parameter. The latter has to be chosen carefully, and the so called L-curve method to find the optimum regularization parameter is outlined. A representative test image is used to study the properties of the inversion scheme with respect to inversion accuracy, amount/strength of regularization and image resolution. The SXR arrays thereby represent an under-determined case while the tangential camera is an over-determined case of the linear inversion problem. In conclusion, it is found that the under-determined case suffers from lack of information but can still return a coarse, but fair image, while the camera data can be well inverted with high resolution.
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1376359
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Purazuma, Kaku Yugo Gakkai-shi
- Additional Journal Information:
- Journal Volume: 93; Journal Issue: 2; Journal ID: ISSN 0918-7928
- Publisher:
- Japan Society of Plasma Science and Nuclear Fusion Research
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 70 PLASMA PHYSICS AND FUSION TECHNOLOGY
Citation Formats
Wingen, Andreas. Regularization of soft-X-ray data in a tokamak application. United States: N. p., 2017.
Web.
Wingen, Andreas. Regularization of soft-X-ray data in a tokamak application. United States.
Wingen, Andreas. Wed .
"Regularization of soft-X-ray data in a tokamak application". United States. https://www.osti.gov/servlets/purl/1376359.
@article{osti_1376359,
title = {Regularization of soft-X-ray data in a tokamak application},
author = {Wingen, Andreas},
abstractNote = {An image inversion scheme for soft X-ray (SXR) diagnostics at the DIII-D tokamak is developed to obtain the local soft X-ray emission at a poloidal cross-section from the spatially line-integrated image taken by either a set of SXR arrays or a tangential camera. The scheme uses the Tikhonov regularization method since the inversion problem is generally ill-posed. The regularization technique uses the generalized singular value decomposition (GSVD) to determine a solution that depends on a free regularization parameter. The latter has to be chosen carefully, and the so called L-curve method to find the optimum regularization parameter is outlined. A representative test image is used to study the properties of the inversion scheme with respect to inversion accuracy, amount/strength of regularization and image resolution. The SXR arrays thereby represent an under-determined case while the tangential camera is an over-determined case of the linear inversion problem. In conclusion, it is found that the under-determined case suffers from lack of information but can still return a coarse, but fair image, while the camera data can be well inverted with high resolution.},
doi = {},
journal = {Purazuma, Kaku Yugo Gakkai-shi},
number = 2,
volume = 93,
place = {United States},
year = {Wed Feb 01 00:00:00 EST 2017},
month = {Wed Feb 01 00:00:00 EST 2017}
}
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