Predicting core transport in ITER baseline discharges with neon injections

TL;DR

This study uses integrated modeling to predict core transport and power exhaust in ITER with neon impurities, identifying conditions that align with divertor protection targets and informing impurity control and heating strategies.

Contribution

First systematic power-flow and impurity-content study for ITER baseline, constrained by existing neon-seeded divertor solutions, providing a self-consistent modeling framework.

Findings

Power crossing the separatrix varies by over 70% across impurity levels.

Optimal $Z_{eff}$ for matching predictions is around 1.6, with reduced auxiliary heating.

Rotation effects alter power crossing by less than 20%.

Abstract

Achieving self-consistent performance predictions for ITER requires integrated modeling of core transport and divertor power exhaust under realistic impurity conditions. We present results from the first systematic power-flow and impurity-content study for the ITER 15 MA baseline scenario constrained directly by existing SOLPS-ITER neon-seeded divertor solutions. Using the OMFIT STEP workflow, stationary temperature and density profiles are predicted with TGYRO for $1.5 \le Z_{\rm eff} \le 2.5$, and the corresponding power crossing the separatrix $P_{\rm sep}$ is evaluated. We find that $P_{\rm sep}$ varies by more than a factor of 1.7 across this scan and matches the $\sim 100$~MW SOLPS-ITER prediction when $Z_{\rm eff} \simeq 1.6$ or when auxiliary heating is reduced to $\sim 75\%$ of nominal. Rotation-sensitivity studies show that plausible variations in toroidal flow magnitude modify $P_{\rm sep}$ by $\lesssim 20\%$, while AURORA modeling confirms that charge-exchange radiation inside the separatrix is dynamically negligible under predicted ITER neutral densities. These results identify a restricted compatibility window, $Z_{\rm eff} \approx 1.6$--1.75 and $0.75 \lesssim f_{P_{\rm aux}} \le 1.0$, in which core transport predictions remain aligned with neon-seeded divertor protection targets. This self-consistent, model-constrained framework provides actionable guidance for impurity control and auxiliary-heating scheduling in early ITER operation and supports future whole-device scenario optimization.