Nuclear Fusion (Jan 2024)

Inter-discharge optimization for fast, reliable access to ASDEX Upgrade advanced tokamak scenario

  • S. Van Mulders,
  • O. Sauter,
  • A. Bock,
  • A. Burckhart,
  • C. Contré,
  • F. Felici,
  • R. Fischer,
  • R. Schramm,
  • J. Stober,
  • H. Zohm,
  • the ASDEX Upgrade Team

DOI
https://doi.org/10.1088/1741-4326/ad1a55
Journal volume & issue
Vol. 64, no. 2
p. 026021

Abstract

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Rapid inter-discharge simulation and optimization using the RAPTOR code have allowed the development of a reliable and reproducible early heating strategy for an advanced tokamak (AT) scenario on ASDEX Upgrade. Solving for electron heat and current diffusion in RAPTOR with ad-hoc formulas for heat transport and electron cyclotron current drive (ECCD) efficiency is found to robustly recover the coupled dynamics of $T_{\mathrm {e}}$ and q , while maintaining model parameters fixed for all discharges. The pedestal top boundary condition in pre-shot simulations is set by a newly derived scaling law for the electron pressure at ρ = 0.8, using a data set of previous AT discharges. RAPTOR simulations have allowed to develop an understanding of the onset of 3/2 tearing modes, which were observed to have a detrimental impact on confinement when low magnetic shear conditions are present at the rational surface during the high- β phase. Delaying the NBI heating, by a specific time interval found via simulations, has led to avoiding these modes. A non-linear optimization scheme has been applied to optimize the ECCD deposition radii to reach a stationary state with $q_{\mathrm {min}} \gt 1$ at the beginning of the flat-top phase, while ensuring a non-zero magnetic shear at q = 1.5 throughout the high- β phase, and has been successfully tested in experiment. However, further experiments, aiming for $q_{\mathrm {min}} \gt 1.5$ , have highlighted limitations of the present feedforward control approach in the presence of shot-to-shot variations that are not included in the applied model. Application of real-time model-based control is proposed to overcome model-reality mismatches in future work.

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