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Title: Regularization of soft-X-ray imaging in the DIII-D tokamak

Abstract

We developed an image inversion scheme for the soft X-ray imaging system (SXRIS) diagnostic at the DIII-D tokamak in order to obtain the local soft X-ray emission at a poloidal cross-section from the spatially line-integrated image taken by the SXRIS 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 to determine a solution that depends on a free regularization parameter. The latter has to be chosen carefully, and the so called {\it 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, image noise and image resolution. Moreover, the optimum inversion parameters are identified, while the L-curve method successfully computes the optimum regularization parameter. Noise is found to be the most limiting issue, but sufficient regularization is still possible at noise to signal ratios up to 10%-15%. Finally, the inversion scheme is applied to measured SXRIS data and the line-integrated SXRIS image is successfully inverted.

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1185689
Alternate Identifier(s):
OSTI ID: 1252799
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Computational Physics
Additional Journal Information:
Journal Volume: 289; Journal Issue: C; Journal ID: ISSN 0021-9991
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; Tikhonov; regularization; image inversion; tokamak; soft X-ray; DIII-D; GSVD

Citation Formats

Wingen, A., Shafer, M. W., Unterberg, E. A., Hill, J. C., and Hillis, D. L. Regularization of soft-X-ray imaging in the DIII-D tokamak. United States: N. p., 2015. Web. doi:10.1016/j.jcp.2015.02.040.
Wingen, A., Shafer, M. W., Unterberg, E. A., Hill, J. C., & Hillis, D. L. Regularization of soft-X-ray imaging in the DIII-D tokamak. United States. https://doi.org/10.1016/j.jcp.2015.02.040
Wingen, A., Shafer, M. W., Unterberg, E. A., Hill, J. C., and Hillis, D. L. Mon . "Regularization of soft-X-ray imaging in the DIII-D tokamak". United States. https://doi.org/10.1016/j.jcp.2015.02.040. https://www.osti.gov/servlets/purl/1185689.
@article{osti_1185689,
title = {Regularization of soft-X-ray imaging in the DIII-D tokamak},
author = {Wingen, A. and Shafer, M. W. and Unterberg, E. A. and Hill, J. C. and Hillis, D. L.},
abstractNote = {We developed an image inversion scheme for the soft X-ray imaging system (SXRIS) diagnostic at the DIII-D tokamak in order to obtain the local soft X-ray emission at a poloidal cross-section from the spatially line-integrated image taken by the SXRIS 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 to determine a solution that depends on a free regularization parameter. The latter has to be chosen carefully, and the so called {\it 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, image noise and image resolution. Moreover, the optimum inversion parameters are identified, while the L-curve method successfully computes the optimum regularization parameter. Noise is found to be the most limiting issue, but sufficient regularization is still possible at noise to signal ratios up to 10%-15%. Finally, the inversion scheme is applied to measured SXRIS data and the line-integrated SXRIS image is successfully inverted.},
doi = {10.1016/j.jcp.2015.02.040},
journal = {Journal of Computational Physics},
number = C,
volume = 289,
place = {United States},
year = {Mon Mar 02 00:00:00 EST 2015},
month = {Mon Mar 02 00:00:00 EST 2015}
}

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Cited by: 14 works
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