Plasma profile reconstruction supported by kineticmodeling

Abstract

Combining the analysis of multiple diagnostics and well-chosen prior information in the framework of Bayesian probability theory, the Integrated Data Analysis code (IDA) can provide density and temperature radial profiles of fusion plasmas. These IDA-fitted measurements are then used for further analysis, such as discharge simulations and other experimental data analysis. Since IDA considers uncertain measurement data from a heterogeneous set of diagnostics, the fitted profiles and their gradients may be in contradiction to well-established expectations from transport theory. Using the modeling suite ASTRA coupled with the quasi-linear transport solver TGLF, we have created a loop in which simulated profiles and their uncertainties are fed back into IDA as an additional prior, thus providing constraints about the physically reasonable parameter space. We apply this physics-motivated prior to several different plasma scenarios and find improved heat flux match, while still matching the experimental data. This work feeds into a broader effort to make IDA more robust against measurement uncertainties or lack of measurements by combining multiple transport solvers with different levels of complexity and computing costs in a multi-fidelity approach.