Solving Poisson equation with slowing-down equilibrium distribution for global gyrokinetic simulation

Qi ZHONG; Yong XIAO

doi:10.1088/2058-6272/ac89cf

Plasma Science and Technology > 2023 > 25(2): 025101. > DOI: 10.1088/2058-6272/ac89cf

Qi ZHONG, Yong XIAO. Solving Poisson equation with slowing-down equilibrium distribution for global gyrokinetic simulation[J]. Plasma Science and Technology, 2023, 25(2): 025101. DOI: 10.1088/2058-6272/ac89cf

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Solving Poisson equation with slowing-down equilibrium distribution for global gyrokinetic simulation

Institute for Fusion Theory and Simulation, Department of Physics, Zhejiang University, Hangzhou 310027, People's Republic of China

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Corresponding author:
Yong XIAO, E-mail: yxiao@zju.edu.cn
Received Date: March 08, 2022
Revised Date: August 02, 2022
Accepted Date: August 14, 2022
Available Online: December 05, 2023
Published Date: January 05, 2023

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Abstract

Abstract

Fusion-born alpha particles in burning plasmas are usually regarded as have a slowing-down distribution, which differs significantly from the Maxwellian distribution of thermal particles in velocity space. A generalized multi-point average method has been developed for gyrokinetic Poisson equation with slowing-down equilibrium distribution using optimization in Fourier space. Its accuracy is verified in both long and short wavelength limits. The influence of changing equilibrium distribution from Maxwellian to slowing-down on gyrokinetic Poisson equation is analyzed to illustrate the significance of the new method. The effect of critical speed in the slowing-down distribution on the field solver is also presented. This method forms an important basis for global gyrokinetic simulation of low-frequency drift Alfvénic turbulence in burning plasmas.
- gyrokinetics,
- Poisson solver,
- slowing-down distribution

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Acknowledgments

This work is supported by the National Magnetic Confinement Fusion Program of China (No. 2015GB110000), and by National Natural Science Foundation of China (No. 11975201).

References (31)

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