A unique experiment in the Joint European Torus (JET) consecutively produced 120 almost identical plasma pulses, providing two orders of magnitude more data than is usually available. This allows the statistical detection of previously unobservable p
henomena such as a sequence of resonant-like waiting times between edge-localised instabilities (ELMs). Here we investigate the causes of this phenomenon. By synchronising data to the 1000s of ELM times and averaging the results, random errors are reduced by a factor of 50, allowing unprecedentedly detailed behaviour to be described. A clear link can then be observed between plasma confinement, ELM occurrence, vertical plasma oscillations, and an otherwise unobservable oscillation in a control coil current that is not usually associated with ELM occurrence. The results suggest a strong and unanticipated edge-plasma dependence on control system behaviour.
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 co
ntrol, 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.
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 distribut
ion 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.
