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Technical Papers

A New Integrated Analysis Suite for Fast-Ion Study in KSTAR

, , , , , , , , , , , & ORCID Icon show all
Pages 151-161 | Received 29 Apr 2022, Accepted 08 Sep 2022, Published online: 19 Dec 2022
 

Abstract

An integrated workflow for fast-ion analysis was developed by adapting the One Modeling Framework for Integrated Task (OMFIT) workflow manager to support a standard and unified analysis platform for KSTAR users. The newly established analysis suite offers a graphical user interface–based workflow to enable users to readily access and handle experimental data archived in various data formats and servers. Further, users can analyze the data by importing modules designed for conducting certain tasks, such as profile fitting, equilibrium reconstruction, and postprocessing of tokamak data. The procedures for preparing the inputs for fast-ion simulations are streamlined by a common workflow manager, which enables the parallel processing of various tasks to efficiently analyze large fast-ion datasets. The OMFIT platform comprises a flexible Python-based application that enables users to freely manipulate the Python scripts for applications that are unavailable in the standard workflow. The framework also offers mapping tools to translate the output data into the Integrated Modeling and Analysis Suite format to maintain application compatibility for future ITER burning plasma experiments.

Acknowledgments

This research was supported by the R&D Program of “KSTAR Experimental Collaboration and Fusion Plasma Research” [Korea Institute of Fusion Energy (KFE) Grant Code: EN2201-13] and “Development of Key Technology and Management of ITER Project” (KFE Grant Code: 2022-IN2204-8) through the KFE funded by government funds. The authors thank J. G. Bak, Y. S. Lee, and W. H. Ko for providing the Mirnov coil, fission chamber, and CES data. Part of the data analysis was performed using the OMFIT integrated modeling frameworkCitation8

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Ministry of Science and ICT [2022-IN2204-8]; Ministry of Science and ICT [EN2201-13].

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