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Analysis techniques for blob properties from gas puff imaging data.

N Offeddu1, C Wüthrich1, W Han2

  • 1EPFL, Swiss Plasma Center (SPC), CH-1015 Lausanne, Switzerland.

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|April 4, 2023
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Summary
This summary is machine-generated.

Researchers analyzed filamentary structures, or blobs, crucial for understanding turbulence and transport in tokamak fusion energy research. New analysis techniques for Gas Puff Imaging data improve the evaluation of blob size, velocity, and frequency.

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Area of Science:

  • Plasma physics
  • Nuclear fusion research
  • Turbulence and transport phenomena

Background:

  • Filamentary structures, or blobs, are key features of plasma turbulence at the edge of magnetically confined plasmas.
  • These structures significantly impact cross-field particle and energy transport, making them critical for tokamak physics and fusion energy development.
  • Existing experimental techniques like stationary probes, passive imaging, and Gas Puff Imaging (GPI) are used to study blob properties.

Purpose of the Study:

  • To present and evaluate novel analysis techniques for 2D Gas Puff Imaging (GPI) data.
  • To assess the performance of these techniques in characterizing filamentary structures (blobs).
  • To compare different analysis methods for their applicability to 2D turbulence data with coherent structures.

Main Methods:

  • Development and application of analysis techniques on 2D GPI data from the Tokamak à Configuration Variable.
  • Utilizing methods such as conditional averaging sampling and individual structure tracking.
  • Implementation and comparison of a recently developed machine learning algorithm for structure analysis.

Main Results:

  • Detailed description and comparison of implemented analysis techniques for blob characterization.
  • Evaluation of blob size, velocity, and appearance frequency using various methods.
  • Assessment of technique applicability based on data requirements and resolution.

Conclusions:

  • The presented techniques offer robust methods for analyzing 2D turbulence data, particularly for intermittent, coherent structures like blobs.
  • The study provides insights into the optimal application scenarios and data requirements for meaningful results in fusion research.
  • These advanced analysis tools enhance the understanding of turbulence and transport in magnetically confined plasmas.