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Plasma current profile reconstruction for EAST based on Bayesian inference

FUSION ENGINEERING AND DESIGN(2021)

Cited 7|Views18
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Abstract
Determining the distribution of plasma current in the equilibrium state is one of the most important steps to realize effective and safe operation of tokamak. In this study, a novel reconstruction code based on Bayesian inference is developed to infer the plasma current distribution for experiment analysis of EAST. Without iteratively solving Grad-Shafranov (G-S) equation to find an optimal fit for the external magnetic diagnostic measurements, the distribution of toroidal current density and poloidal flux can be rapidly derived in a probabilistic manner. The reconstructed results are consistent with the results based on equilibrium fitting (EFIT) code, and the execution time is less than 1 ms for each time slice, which indicates its potential for application in future realtime plasma feedback control.
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Key words
Machine learning,Bayesian inference,Plasma equilibrium reconstruction,Tomography,EAST
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