An integrated data analysis tool for improving measurements on the MST RFP

Area of Science:

• Plasma physics
• Fusion energy research
• Diagnostic instrumentation

Background:

• Plasma diagnostics often provide complementary data.
• Electron temperature is a key plasma parameter.
• The Madison Symmetric Torus utilizes multiple diagnostics like soft x-ray (SXR) and Thomson Scattering (TS).

Purpose of the Study:

• To develop a systematic method for integrating complementary plasma diagnostic data.
• To enhance the accuracy and sensitivity of electron temperature measurements.
• To create a more robust data analysis tool for fusion devices.

Main Methods:

• Integrated data analysis based on Bayesian probability theory.
• Application of a Markov Chain Monte Carlo (MCMC) analysis for increased flexibility.
• Benchmarking the MCMC method against a grid search approach.

Main Results:

• An integrated data analysis tool successfully estimated electron temperatures consistent with both SXR and TS diagnostics.
• The integrated approach yielded more precise electron temperature measurements than individual diagnostics.
• The MCMC analysis provided a flexible and effective enhancement to the integrated tool.

Conclusions:

• Combining complementary plasma diagnostic data significantly improves measurement accuracy and precision.
• Bayesian-based integrated data analysis is a powerful technique for plasma research.
• Advanced computational methods like MCMC enhance the capabilities of integrated diagnostic tools.