Estimating cross-field particle transport at the outer midplane of TCV by tracking filaments with machine learning
W. Han, N. Offeddu, T. Golfinopoulos, C. Theiler, J. L. Terry, C. Wüthrich, D. Galassi, C. Colandrea, E. S. Marmar
Abstract
Abstract Cross-field transport of particles in the boundary region of magnetically confined fusion plasmas is dominated by turbulence. Blobs, intermittent turbulent structures with large amplitude and a filamentary shape appearing in the scrape-off layer (SOL), are known from theoretical and experimental studies to be the main contributor to the cross-field particle transport. The dynamics of blobs differs depending on various plasma conditions, including triangularity ( δ ). In this work, we analyze triangularity dependence of the cross-field particle transport at the outer midplane of plasmas with <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>δ</mml:mi> <mml:mo>=</mml:mo> <mml:mo>+</mml:mo> <mml:mn>0.38</mml:mn> </mml:math> , +0.15, −0.14, and −0.26 on the Tokamak à Configuration Variable, using our novel machine learning (ML) blob-tracking approach applied to gas puff imaging data. The cross-field particle flux determined in this way is of the same order as the overall transport inferred from KN1D, GBS, and SOLPS-ITER simulations, suggesting that the blobs identified by the ML blob-tracking account for most of the cross-field particle transport in the SOL. Also, the ML blob-tracking and KN1D show a decrease in the cross-field particle transport as δ becomes more negative. The blob-by-blob analysis of the result from the tracking reveals that the decrease of cross-field particle transport with decreasing δ is accompanied by a decrease in the number of blobs in a fixed time, which tend to have larger area and lower radial speed. Also, the blobs in these plasmas are in the connected sheath regime, and show a velocity scaling consistent with the two-region model.