Master Thesis

Goal

The goal of this master thesis is to study the transport physics in ASDEX Upgrade tokamak plasmas using a newly implemented interpretative transport code in the Integrated Data Analysis (IDA) framework. This implementation is intended to provide the electron and ion transport coefficients (diffusion coefficients chi_e and chi_i) routinely shortly after a plasma discharge without employing sophisticated, but numerically expensive transport codes. Typically in transport studies, the transport coefficients are estimated by costly transport codes and the kinetic profiles (ne, Te, Ti) are estimated. These are then compared to the measured kinetic profiles, and the transport coefficients as derived from power balance calculations. These calculations are very sensitive to the difference between the ion and electron temperatures, which can become very similar at the plasma edge. Hence, power balance estimates of the ion and electron heat diffusivity in the edge region, and in the edge pedestal require very careful alignment of the profiles and attention to the uncertainties on the measurements. Within the new IDA framework, the uncertainties on the measurements are automatically included and hence can be propagated to the derived transport coefficients. However, uncertainty remains on the radial alignment of the ne, Te, and Ti profiles. To assess the reliability of the automatic analysis provided by the IDA framework, the analysis should be applied to a set of discharges in which the relative alignment of the profiles is systematically varied within the uncertainties and the impact on chi_e and chi_i documented. The objective would be to determine under which conditions the automatic analysis can be trusted and out to which radial position. The chosen set of discharges should, ideally, cover a wide range of conditions seen in the experiment. Once the reliability of the analysis is assessed, the determined transport coefficients in the outer core region (0.7<rho>0.95) can be compared to predictions of the coefficients from ASTRA-TGLF, to determine how well the predictive model can reproduce the measured profiles and transport.