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Non-equilibrium Microwave Plasma for Efficient High Temperature Chemistry

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Application of random sample consensus method for parameter estimation of reflectometry density profile in toroidal

K X Ye¹, T Zhang¹, Y M Wang¹

¹Institute of Plasma Physics, and Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui 230031, People's Republic of China.

The Review of Scientific Instruments

|July 10, 2021

Summary

A new RANSAC algorithm improves plasma density profile analysis from microwave reflectometry, overcoming turbulence challenges. The GA-RANSAC method offers enhanced robustness and convergence for fusion plasma diagnostics.

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Area of Science:

Plasma physics
Fusion energy research
Diagnostic techniques

Background:

Microwave reflectometry is crucial for measuring fusion plasma density profiles.
Plasma turbulence causes significant deviations, complicating accurate profile evaluation.
Existing methods struggle with the robustness required for edge plasma diagnostics.

Purpose of the Study:

To enhance the accuracy and reliability of plasma density profile evaluation.
To address challenges posed by plasma turbulence in reflectometry data.
To introduce advanced computational methods for improved profile fitting.

Main Methods:

Application of a modified RANdom SAmple Consensus (RANSAC) algorithm to fit density profiles.
Utilizing reflectometry data from the experimental advanced superconducting tokamak.
Developing and implementing a Genetic Algorithm-RANSAC (GA-RANSAC) hybrid method for further optimization.

Main Results:

The modified RANSAC method demonstrated superior efficiency and robustness compared to traditional least-squares fitting.
The GA-RANSAC approach showed improved performance and stabler convergence over the modified RANSAC alone.
Accurate fitting of challenging edge density profiles was achieved.

Conclusions:

The modified RANSAC method significantly enhances the evaluation of fusion plasma density profiles.
The GA-RANSAC hybrid method represents a state-of-the-art approach for robust and accurate plasma diagnostics.
These advancements are critical for understanding and controlling fusion plasmas.