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conference presentation

ITER baseline scenario investigations on TCV and comparison with AUG

Sauter, Olivier  orcid-logo
•
Vallar, Matteo  
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May 15, 2021
28th IAEA Fusion Energy Conference

Under the auspices of EUROfusion (WPMST1), the ITER baseline scenario (IBL, [1]) is jointly investigated on AUG and TCV. While the AUG results were presented at the last IAEA FEC [2], this contribution focuses on the recent results obtained in TCV and related integrated modelling results. Such developments in TCV were only possible with the installation of an NBI heating source [3], allowing ELMy H-modes at ITER relevant N. The IBL scenario is mainly characterized by low q95 (3.0-3.6), high positive triangularity (>0.35) and relatively high elongation (>1.65) and normalized beta (N>1.5). In AUG, these combinations lead to very steep and narrow edge transport barriers, when good confinement is obtained, with high pedestal pressure and therefore large type-I ELM crashes. A similar behaviour is also observed on TCV where discharges with similar confinement properties (H98~1) and normalized beta (N~1.8), as those expected for the ITER baseline scenario, have been obtained. TCV IBL performance is mainly limited by (neoclassical) tearing modes, in particular 2/1 modes. We show that they can be avoided with central X3 EC heating at relatively high q95 and moderate N. However, the lack of significant ECH at the high central densities obtained in TCV IBL scenario limits the duration of low q95 cases to about six confinement times. During this time, current density can fully evolve and density usually keeps peaking until (neoclassical) tearing modes are triggered. Integrated modelling results show ITG dominant instabilities in both AUG and TCV IBLs, and show that, in TCV, NBI fuelling also plays a role to sustain the mainly turbulent-driven significant peaked density profiles. The role of profiles, sawteeth and ELMs regarding MHD stability are also discussed. Safe termination of AUG IBL is demonstrated, q95~3 included, consistent with predictive optimization using RAPTOR

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Sauter_reprint0887_IAEA_2021.pdf

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http://purl.org/coar/version/c_71e4c1898caa6e32

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