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    Turbulent particle and thermal transport in magnetized plasmas

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    FU-DISSERTATION-2013.pdf (3.159Mb)
    Date
    2013-05
    Author
    Fu, Xiangrong
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    Abstract
    The particle and thermal transport by low-frequency drift waves in magnetized plasmas are studied with theories and simulations. Universal in inhomogeneous plasmas, drift waves in Earth's ionosphere, the GAMMA-10 Tandem Mirror machine, the Columbia Linear Machine and C-Mod tokamak are studied in this thesis. The first investigations are E x B particle transport in the given electric and magnetic fields of the GAMMA-10 mirror machine at the University of Tsukuba in Japan. The results show that the formation of E [subscript r]-shear by local heating of electrons can reduced the radial particle loss. The turbulent impurity particle transport driven by various modes in the MIT tokamak Alcator C-Mod is studied by a quasilinear theory and compared to experimental measurement of Boron density profiles. A code is developed for solving eigensystems of drift wave turbulence equations for the multi-component fusion plasmas and calculating quasilinear particle fluxes. The calculations are much faster than nonlinear simulations and may be suitable for real-time analysis and feedback control of tokamak plasmas. The electron temperature gradient (ETG) mode is a candidate mechanism for anomalous electron thermal transport across various magnetic confinement geometries. This mode was produced in the Columbia Linear Machine (CLM) at Columbia University. Large scale simulations of the ETG mode in the CLM by a gyrokinetic code GTC are carried out on supercomputers at TACC and NERSC. The results show good agreement with experiments in the dominant mode number, wave frequencies and the radial structure. Some nonlinear properties are also analyzed using the code.
    Department
    Physics
    Description
    text
    Subject
    Turbulence
    Transport
    Drift waves
    Plasma
    Fusion
    URI
    http://hdl.handle.net/2152/21657
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    • facebook
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    • CONTACT US
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    © The University of Texas at Austin