Statistical analysis and modeling of intermittent transport events in the tokamak SOL

TL;DR

This paper investigates the statistical properties of intermittent, bursty turbulence events in the tokamak scrape-off-layer, combining fluid simulations with theoretical modeling to understand their probability distributions and impact on heat load predictions.

Contribution

It introduces a first-principles theoretical model for the tails of the probability distribution functions of turbulent events in the tokamak SOL, validated against fluid simulation data.

Findings

Probability distribution functions have strong exponential tails.

Simulation results agree with the analytical theoretical predictions.

Intermittent events significantly influence heat load estimates.

Abstract

The turbulence observed in the scrape-off-layer of a tokamak is often characterized by intermittent events of bursty nature, a feature which raises concerns about the prediction of heat loads on the physical boundaries of the device. It appears thus necessary to delve into the statistical properties of turbulent physical fields such as density, electrostatic potential and temperature, focusing on the mathematical expression of tails of the probability distribution functions. The method followed here is to generate statistical information from time-traces of the plasma density stemming from Braginskii-type fluid simulations, and check this against a first-principles theoretical model. The analysis of the numerical simulations indicates that the probability distribution function of the intermittent process contains strong exponential tails, as predicted by the analytical theory.