Improved atomic data and collisional-radiative modeling for magnetic fusion plasmas
ORAL
Abstract
The availability of precise and complete atomic data, such as level energies and cross-sections of different atomic processes, is essential for accurate modeling of the magnetic fusion plasmas. Despite considerable efforts in producing reliable atomic data, computational limitations and approximations used in different theoretical approaches have led to significant gaps, especially for near-neutral or low-electron-temperature plasmas. In this study, we present improved atomic data including the cross-sections of different atomic processes obtained using state-of-the-art theoretical approaches, such as the convergent close-coupling and R-matrix methods. These refined atomic data are subsequently incorporated into detailed collisional-radiative (CR) models. Specifically, we have developed fine-structure CR models for low-Z plasma species, while for high-Z plasma species, hybrid CR models are constructed by combining the optimized sets of fine-structure and configuration-averaged/superconfiguration atomic states and data. These advanced CR models are employed to compute precise plasma parameters, such as atomic/ionic populations, radiative power loss, average charge state, and effective charge state, over a wide range of electron temperatures and electron densities. The comparison emphasizes the critical need for highly accurate complete atomic data and advanced CR models to understand the complex dynamics of the atomic processes in magnetic fusion plasmas.
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Presenters
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Prashant Sharma
Los Alamos National Laboratory
Authors
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Prashant Sharma
Los Alamos National Laboratory
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Christopher J Fontes
Los Alamos National Laboratory, Los Alamos National Laboratory (LANL)
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Dmitry V Fursa
Curtin Univ of Technology
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Igor Bray
Curtin Univ of Technology
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Mark C Zammit
Los Alamos National Laboratory
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James P Colgan
Los Alamos National Laboratory
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Hyun-Kyung Chung
Korea Institute of Fusion Energy (KFE)
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Nathan Garland
Griffith University
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Xianzhu Tang
Los Alamos National Laboratory, Los Alamos Natl Lab