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QLKNN

Fast modeling of turbulent transport in fusion plasmas using neural networks

Paper title Fast modeling of turbulent transport in fusion plasmas using neural networks

van de Plassche et al. (DIFFER) · Energy & fusion · Public: code, data, weights

Paper arXiv 1911.05617PDF

QLKNN is a set of feed-forward networks that reproduce the heat and particle fluxes of the quasilinear gyrokinetic transport model QuaLiKiz from nine local plasma parameters. The training enforces known physics, such as a sharp critical gradient below which turbulent flux is zero. The networks replace QuaLiKiz inside the tokamak simulators JINTRAC and RAPTOR.

Published
Physics of Plasmas

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