Reconstruction of the emissivity and flow for Doppler coherence imaging spectroscopy (CIS) on J-TEXT

Li, Bingli; Wang, Tianbo; Nie, Lin; Long, Ting; Zhang, Xiaoyi; Sharples, R.M.; Xu, Min; Wang, Zhanghui; Chen, Zhipeng; Wu, Hao; Liu, Zijie; Ke, Rui; Zhang, Xiaolong; Jiao, Shaodong; Qing, Wanjun; Tian, Ye; Pan, Yuan

Abstract

Doppler coherence imaging spectroscopy (CIS) has been installed on J-TEXT tokamak to provide a wealth of information for carbon impurity ions (CIII). To obtain the local emissivity and flow from the line-integrated information measured by the camera, the tomographic inversion needs to propose. However, besides the ill-conditioned nature of the inversion, the distribution of CIII (only in the narrow scrape-off-layer (SOL) and around the divertor) makes the inversion more challenging. And the error in the emissivity inversion may propagate to the flow inversion. In this article, we have introduced the two classical tomographic algorithms, Tikhonov regularization, and minimum Fisher information regularization. To estimate the uncertainty of these algorithms and study the error sources, two typical CIII distribution models were chosen to make benchmarks. Finally, these methods were applied to a J-TEXT experiment, demonstrating the emissivity and flow distribution in SOL and around the divertor.

Citation

Li, B., Wang, T., Nie, L., Long, T., Zhang, X., Sharples, R., Xu, M., Wang, Z., Chen, Z., Wu, H., Liu, Z., Ke, R., Zhang, X., Jiao, S., Qing, W., Tian, Y., & Pan, Y. (2022). Reconstruction of the emissivity and flow for Doppler coherence imaging spectroscopy (CIS) on J-TEXT. Fusion Engineering and Design, 184, Article 113271. https://doi.org/10.1016/j.fusengdes.2022.113271

• Journal Article Type: Article
• Acceptance Date: Aug 19, 2022
• Online Publication Date: Sep 19, 2022
• Publication Date: 2022-11
• Deposit Date: Jan 23, 2023
• Journal: Fusion Engineering and Design
• Print ISSN: 0920-3796
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 184
• Article Number: 113271
• DOI: https://doi.org/10.1016/j.fusengdes.2022.113271
• Public URL: https://durham-repository.worktribe.com/output/1182286