Model-based electron density estimation using multiple diagnostics on TCV

Abstract

Estimation of the dynamic evolution of the electron plasma density during a tokamak discharge is crucial since it directly affects the plasma performance, confinement and stability. Therefore it needs to be monitored and controlled. Knowledge of the density profile can also be used to control in a more direct way the desired aspects of the plasma density, for example choosing to control the core, volume averaged or edge density, replacing control methods that rely e.g. on a single line-averaged electron density from a specific interferometer chord. The reconstruction of the density profile can be performed with the RAPDENS code, employing the Extended Kalman Filter (EKF) technique. The code collects the electron plasma density measurements from the available real-time diagnostics and uses them to constrain the solution of a predictive model that describes the 1D particle transport equation for the electron plasma density.Following recent improvements to the code for use on ASDEX-Upgrade, we report on the application of this method for the reconstruction of density profiles in the TCV tokamak using low-frequency Thomson Scattering measurements and high-frequency interferometer measurements simultaneously, both of which are available in real-time. We show how to treat the time-varying relation between the measurements and the density profile due to the evolving equilibrium. Additionally, we show a method to compensate for offsets in interferometer measurements in real-time using Thomson Scattering information.