Abstract Details
Abstracts
Author: Juan M Losada
Requested Type: Consider for Invited
Submitted: 2022-03-04 04:22:33
Co-authors: A. Theodorsen, O. E. Garcia
Contact Info:
UiT The Arctic University of Norway
Dalvegen 19
Kvaløya, Troms 9107
Norway
Abstract Text:
A stochastic model has been developed describing the dynamics of intermittent fluctuations due to radial motion of coherent blob-like structures in the scrape-off layer (SOL) of magnetically confined plasma. Uncorrelated pulses move radially outwards with a random distribution of amplitudes, sizes, velocities and arrival times. The pulses have a fixed shape and an exponentially decaying amplitude due to parallel drainage towards the divertor plates. In its simplest form, the model leads to exponentially decaying average radial profiles [1, 2]. More generally, we study the implications of correlations between filament parameters on mean profiles and higher-order moments. A broad distribution of pulse velocities leads to non-exponential profiles and strongly increased intermittency in the far SOL. It is demonstrated that this explains many features from experimental measurements.
In addition, the stochastic model can be employed in the development of new data analysis techniques. In particular, we study the effects of a velocity distribution on cross-correlation measurements which are routinely employed in experimental data [3]. Our findings show that certain filament velocity distributions lead to cross-correlation functions that underestimate the average velocity, and thus leave traditional cross-correlation techniques erroneous. Moreover, within the framework provided by the stochastic model, we develop techniques to estimate filament velocity distributions that remain unbiased. Examples will be presented where the novel cross-correlation technique is applied to experimental measurement data as well as numerical turbulence simulations.
These results may help understand and interpret the dynamics of intermittent fluctuations in the scrape-off layer. Thus, our model will bridge more complex, first-principle based theories and experiments.
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