Universal statistical description of turbulent transport for flux driven toroidal plasmas
Paper in proceedings, 2016
During recent years an overwhelming body of evidence show that the overall transport of heat and particles is to a large part caused by intermittency (or bursty events) related to coherent structures. A crucial question in plasma confinement is thus the prediction of the probability distribution func-tions (PDFs) of the transport due to these structures and of their formation. This work provides a theoretical interpretation of numerically generated probability density functions (PDFs) of intermit-tent plasma transport events as well as offering an explanation for elevated PDF tails of heat flux. Specifically, in this work we analyse time traces of heat flux generated by global nonlinear gyroki-netic simulations of ion-temperature-gradient turbulence by the GKNET software . The simula-tion framework is global, flux-driven and considers adiabatic electrons. In these simulations SOC type intermittent bursts are frequently observed and transport is often regulated by non-diffusive processes, thus the PDFs of e.g. heat flux are in general non-Gaussian with enhanced tails. A key finding of this work is that the intermittent process in the context of drift-wave turbulence appears to be independent of the specific modelling framework, opening the way to the prediction of its sa-lient features. Although, the same PDFs were previously found in local gyrokinetic simulations  there are some unique features present inherently coming from the global nature of the physics. The main part of this work consists in providing a theoretical interpretation of the PDFs of radial heat flux derived by nonlinear, global, gyrokinetic simulations of drift-wave turbulence in tokamaks. The numerically generated time traces are processed with Box–Jenkins modelling in order to re-move deterministic autocorrelations, thus retaining their stochastic parts only. These PDFs have been shown to agree very well with analytical predictions based on a fluid model, on applying the instanton method. The result points to a universality in the modelling of intermittent stochastic pro-cess while the analytical theory offers predictive capability, extending the previous result to be globally applicable.