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Using integrated data analysis to extend measurement capability (invited).

L M Reusch1, M D Nornberg1, J A Goetz1

  • 1University of Wisconsin-Madison, Madison, Wisconsin 53706, USA.

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|November 8, 2018
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Summary
This summary is machine-generated.

Integrated Data Analysis (IDA) maximizes information from multiple data streams for precise plasma parameter inference. This approach overcomes limitations of single-diagnostic methods, crucial for future fusion energy research.

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Area of Science:

  • * Plasma Physics
  • * Fusion Energy Research

Background:

  • * Traditional methods use single diagnostics for plasma parameter measurement, discarding valuable information.
  • * Diagnostics like Thomson scattering capture data beyond their primary target, such as background light.
  • * This unused data contains information on parameters like effective charge (Zeff).

Purpose of the Study:

  • * To introduce Integrated Data Analysis (IDA) as a superior method for plasma parameter inference.
  • * To highlight IDA's capability to utilize all available information from multiple raw data streams.
  • * To demonstrate how IDA enhances spatial/temporal resolution and measurement accuracy.

Main Methods:

  • * Integrated Data Analysis (IDA) framework.
  • * Exploitation of information from multiple diagnostic data streams.
  • * Quantitative analysis of all data, including background signals.

Main Results:

  • * IDA enables more precise inference of plasma parameters compared to single-diagnostic approaches.
  • * Achieved improved spatial and temporal resolution in measurements.
  • * Successfully measured parameters like Zeff, which are challenging for single diagnostics, as demonstrated on the Madison Symmetric Torus.

Conclusions:

  • * IDA is essential for maximizing data utility in plasma physics.
  • * The approach is critical for accurate measurements in the upcoming burning plasma era.
  • * Limited diagnostic access in harsh fusion environments necessitates IDA's comprehensive data exploitation.