Data adaptive control parameter estimation for scaling laws for magnetic fusion devices

Data Adaptive Planning determines the expected utility of a single new measurement using existing data and a data descriptive model. The method can be used for experimental planning. It is applied to scaling laws for magnetic fusion devices. Explicitly, the scaling of the stellarator W7-AS is examined for a subset of t = 1/3 data. In control parameter space regions of high utility are identified and serve for fixing discharge and machine parameters for upcoming discharges. It will be shown that a skillful analysis of experimental uncertainties is of utmost importance for significant results. (authors)