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For a two week period during the Joint European Torus (JET) 2012 experimental campaign, the same high confinement plasma was repeated 151 times. The dataset was analysed to produce a probability density function (pdf) for the waiting times between edge-localised plasma instabilities (ELMS). The result was entirely unexpected. Instead of a smooth single peaked pdf, a succession of 4-5 sharp maxima and minima uniformly separated by 7-8 millisecond intervals was found. Here we explore the causes of this newly observed phenomenon, and conclude that it is either due to a self-organised plasma phenomenon or an interaction between the plasma and a real-time control system. If the maxima are a result of resonant frequencies at which ELMs can be triggered more easily, then future ELM control techniques can, and probably will, use them. Either way, these results demand a deeper understanding of the ELMing process.
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The generic question is considered: How can we determine the probability of an otherwise quasirandom event, having been triggered by an external influence? A specific problem is the quantification of the success of techniques to trigger, and hence control, edge-localised plasma instabilities (ELMs) in magnetically confined fusion (MCF) experiments. The development of such techniques is essential to ensure tolerable heat loads on components in large MCF fusion devices, and is necessary for their development into economically successful power plants. Bayesian probability theory is used to rigorously formulate the problem and to provide a formal solution. Accurate but pragmatic methods are developed to estimate triggering probabilities, and are illustrated with experimental data. These allow results from experiments to be quantitatively assessed, and rigorously quantified conclusions to be formed. Example applications include assessing whether triggering of ELMs is a statistical or deterministic process, and the establishment of thresholds to ensure that ELMs are reliably triggered.
Global electromagnetic gyrokinetic simulations show the existence of near threshold conditions for both a high-$n$ kinetic ballooning mode (KBM) and an intermediate-$n$ kinetic version of peeling-ballooning mode (KPBM) in the edge pedestal of two DIII-D H-mode discharges. When the magnetic shear is reduced in a narrow region of steep pressure gradient, the KPBM is significantly stabilized, while the KBM is weakly destabilized and hence becomes the most-unstable mode. Collisions decrease the KBMs critical $beta$ and increase the growth rate.
The statistics of edge-localised plasma instabilities (ELMs) in toroidal magnetically confined fusion plasmas are considered. From first principles, standard experimentally motivated assumptions are shown to determine a specific probability distribution for the waiting times between ELMs: the Weibull distribution. This is confirmed empirically by a statistically rigorous comparison with a large data set from the Joint European Torus (JET). The successful characterisation of ELM waiting times enables future work to progress in various ways. Here we present a quantitative classification of ELM types, complementary to phenomenological approaches. It also informs us about the nature of ELMing processes, such as whether they are random or deterministic.
Decay times of plasma flows and plasma profiles have been measured after a sudden biasing switch-off in experiments on the CASTOR tokamak. A biased electrode has been used to polarize the edge plasma. The edge plasma potential and flows have been characterized by means of Langmuir and Mach probes, the radiation was measured using an array of bolometers. Potential profiles and poloidal flows can be well fitted by an exponential decay time in the range of 10 - 30 microseconds when the electrode biasing is turn off in the CASTOR tokamak. The radiation shows a slower time scale (about 1 ms), which is linked to the evolution in the plasma density and paticle confinement.
The stochastic layer formation by the penetration of the resonant magnetic perturbation (RMP) field has been considered as a key mechanism in the RMP control of the edge localized mode (ELM) in tokamak plasmas. Difficulty in quantifying the stochasticity has limited the assessment of the stochastic field effect in the pedestal transport to ambiguous inference from the pressure profile change. Here, we suggest the rescaled complexity for an effective measure of the stochasticity in the fluctuation and transport. This could be used to identify the narrow and localized stochastic layer around the pedestal top and estimate its width. We found that the fluctuation and transport in the edge plasmas become more stochastic with the more penetration of the RMP field into the plasma, which supports the importance of the stochastic layer formation in the RMP ELM control experiment.
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