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Reconstruction of microturbulence wave number spectra from radial correlation reflectometry data

Abstract : Turbulence is supposed to be the main source of anomalous transport in tokamaks which leads to loss of heat much faster than as it is predicted by neoclassical theory. Development of plasma turbulence diagnostics is one of the key issues of nuclear fusion to control turbulent particles and energy transport in a future fusion power station. Diagnostics based on microwaves scattered from plasma attract attention of researchers as non-disturbing and requiring just a single access to plasma. The phase of the reflected wave contains information on the position of the cut-off layer and density fluctuations. Correlation reflectometry is now a routinely used technique providing information on plasma microturbulence. Although the diagnostics is widely spread data interpretation remains quite a complicated task. Thus, it was supposed that the distance at which the correlation of two signals received from plasma is suppressed is equal to the turbulence correlation length. However this approach is incorrect and introduces huge errors to determined plasma microturbulence parameters. The aim of this thesis is to develop an analytical theory, to give a correct interpretation of radial correlation reflectometry (RCR) data and to provide researchers with simple formulae for extracting information on microturbulence parameters from RCR experiments. Numerical simulations based on the theory prove applicability of this theoretical method and give an insight for experimentalists on its capability and on optimized diagnostic parameters to use. Furthermore the results obtained on three different machines are carefully analyzed and compared with theoretical predictions and numerical simulations as well
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https://hal.univ-lorraine.fr/tel-01749371
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  • HAL Id : tel-01749371, version 1

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Natalia Kosolapova. Reconstruction of microturbulence wave number spectra from radial correlation reflectometry data. Other [cond-mat.other]. Université de Lorraine, 2012. English. ⟨NNT : 2012LORR0132⟩. ⟨tel-01749371⟩

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