Development And Applications Of Synthetic Microwave Imaging Reflectometry Mir Diagnostics
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Development and Applications of Synthetic Microwave Imaging Reflectometry (MIR) Diagnostics
Author | : Xiaoxin Ren |
Publisher | : |
Total Pages | : |
Release | : 2016 |
Genre | : |
ISBN | : 9781369201437 |
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The Tokamak is one of the most-researched candidates for producing controlled thermonuclear fusion power. Its confinement quality is highly limited by micro-scale as well as MHD turbulence in plasma. The UC Davis Millimeter-Wave group is dedicated to the development of tools, mainly Electron Cyclotron Emission Imaging (ECEI) and Microwave Imaging Reflectometry (MIR) to diagnose turbulence in plasmas. Here, ECEI and MIR are used to diagnose temperature and density fluctuations in the cross section of a Tokamak. In this dissertation, the focus is on the development of the MIR system, and more specifically, on the development and applications of a synthetic MIR diagnostic. The synthetic MIR helps in the design stage by optimizing and validating optical lens parameters of the imaging system. It also helps to determine the possible operating space of a MIR system. With the help of synthetic MIR, an MIR system was successfully installed on the DIII-D Tokamak. MIR then achieved great performance in measuring a wide range of MHD instabilities, for instance, strong inter-ELM modes in H-mode operation plasmas. Synthetic MIR then helps to interpret experimental data, and was used for edge harmonic oscillation studies and provides a proxy between the plasma simulation codes and real plasma. This dissertation first emphasizes the importance of fusion and fusion turbulence diagnostics; it then covers the principles of the MIR system, the hardware of the DIII-D MIR system, and then goes deeply into the process of synthetic MIR. Afterwards, the dissertation focuses on the analytical results from synthetic MIR simulations for defining the MIR instrumental function, and also how it helped to calibrate the DIII-D MIR system and interpret experimental data. Then, the dissertation concludes with future software and hardware upgrades for both synthetic and real MIR systems.
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