Evaluation of impurity densities from charge exchange recombination spectroscopy measurements at ASDEX Upgrade

Abstract

At ASDEX upgrade (AUG) a new framework for the evaluation of impurity densities based on measurements from charge exchange recombination spectroscopy (CXRS) diagnostics has been developed. The charge exchange impurity concentration analysis code, or CHICA, can perform these calculations for all of the beam-based CXRS diagnostics at AUG and is equipped with the atomic data for all of the regularly measured charge exchange spectral lines (He, Li, B, C, N, O, and Ne). CHICA includes four different methods for the evaluation of the neutral density populations, which feature different implementations and contain varying levels of sophistication. These methods have been thoroughly benchmarked against one another, enabling the important processes for the evaluation of neutral densities to be identified as well as the neutral populations that are most critical to the accurate interpretation of the measured CXRS intensities. For the AUG neutral beams, charge exchange with the ground state of the first energy component is typically the dominant contribution to the measured CXRS intensities, but emission from reactions with the n=2 beam halo population can contribute up to 35% to the total signal and must be included in the analysis. Neglect of this population leads to incorrect magnitudes and incorrect profile shapes of the calculated impurity density profiles. The edge lines of sight (LOS) of the core CXRS diagnostics at AUG intersect the edge pedestal inside of the neutral beam volume. Therefore, the impurity density is not constant along the LOS, complicating the interpretation of the measured intensities. Within CHICA a forward model for the edge impurity densities has been implemented, enabling the reconstruction of accurate edge profiles.

Charge exchange recombination spectroscopy at Wendelstein 7-X

“…Nonetheless, calculation of the absolute concentration must still take into account all energy components, the relative sensitivity of the spectrometer channels, the effective charge exchange and beam emission coefficients and their dependence on the local plasma parameters. Also, at higher densities, a significant contribution to charge exchange also originates from the n = 2 states of the beam halo 34 , which necessitates an accurate model of the halo as this is not accounted for by the relative intensity ratio method.…”

“…A thorough analysis of the impurity concentration profiles and transport during the last W7-X campaign is underway 35 and will use both this relative CX/BES intensity method as well as the modelled absolute beam and halo densities 34 to derive accurate absolute impurity profiles of the low-Z impurities present in W7-X including carbon, oxygen and boron that was introduced for wall conditioning 36 .…”

“…Figure 11 (green) shows the normalised carbon concentration profiles at the start (a) and end (b) of a pure NBI phase, revealing strong peaking of the carbon concentration in the plasma core during pure NBI operation. Given the high electron densities reached at the end of such pure NBI phases, the halo could contribute up to 50% of the signal in the core 34 . However, even at this level, it could only account for a small amount of the observed intensity peaking.…”

Electron capture, ionization and excitation cross sections for keV collisions between fully stripped ions and atomic hydrogen in ground and excited states

“…The hydrogen atoms introduced in the plasmas are in their ground electronic state. However, electronically excited atomic hydrogen can be found in the halo of the beam and collisions with these excited species may contribute significantly to the signals measured for the plasma diagnosis [5].…”

Measuring the plasma composition in tokamaks with metallic plasma-facing components

“…Over the decades, various spectroscopic diagnostics and analysis methodologies have been developed to estimate the impurity densities and plasma effective charge (see e.g. Behringer et al (1986), Rathgeber et al (2010), Czarnecka et al (2011), Pütterich et al (2012), Reinke et al (2012), Coenen et al (2013), McDermott et al (2018), Odstrcil et al (2018), Sertoli et al (2018) and reference therein) and on these results depend the conclusions drawn by complex analysis and modelling of present experiments as well as predictions for future machines such as ITER or DEMO (see e.g. Dux & Peeters (2000), Kallenbach et al (2005), Pacher et al (2007), Delgado-Aparicio et al (2011), Lerche et al (2011), Tardini et al (2012), , Kallenbach et al (2013), Zagórski, Ivanova-Stanik & Stankiewicz (2013), Loarte et al (2015) and Breton et al (2018a)).…”