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Model reduction for tokamak plasma turbulence : beyond fluid and quasi-linear descriptions

Abstract : The optimization and control of tokamak plasmas requires predicting the transport of matter and heat in a way that is both efficient and accurate. Triggered by kinetic instabilities, turbulence saturates through the interaction of several scales. From the small scale of vortices, to the feedback on the profiles, passing through the spontaneous generation of zonal flows and the ballistic transit of avalanches, everything conspires and self-organizes. First-principles simulation codes like GYSELA solve the evolution of the gyro-kinetic distribution function. This path may be faithful, but it is insufficiently effective. The description should be reduced. The suppression of velocity dimensions occurs through the problem of the non-collisional closure of fluid equations. Previous approaches are extended and generalized by drawing on the literature of dynamic systems analysis and control theory. In particular, we apply the methods of reduction by balanced truncation and by rational interpolation to the one-dimensional linear Vlasov–Poisson model. The interpolation method is distinguished by its low cost and ease of use, opening up prospects for modeling more complex phenomena.
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Camille Gillot. Model reduction for tokamak plasma turbulence : beyond fluid and quasi-linear descriptions. Physics [physics]. Aix Marseille Université, 2020. English. ⟨tel-03636771⟩

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