Model-Based Optimization of the Field-Null Configuration for Robust Plasma Breakdown on the HL-3 Tokamak
This paper introduces a self-consistent field-null optimization algorithm of a poloidal magnetic field that precisely accounts for the influence of vacuum vessel eddy currents. Building on existing poloidal field (PF) coil currents, the algorithm can refine these waveforms to achieve various target field-null configurations. Firstly, based on the TokSys toolbox, a response model, including the PF coils and vacuum vessel circuits for the HL-3 tokamak, is developed under the MATLAB® and Simulink™ framework. The resistivity parameters of the model are calibrated using experimental data obtained from single-coil discharge tests. Subsequently, an iterative method was employed to simultaneously solve the dynamic field-null optimization problem within a specified spatial region and precisely account for the effect of passive eddy currents. Typically, B⊥≤1 G within a large area can be obtained with this iterative scheme, which can be stably sustained for over 15 milliseconds to ensure the robustness of breakdown. Finally, a low-pass filtered PID controller is applied to the model to achieve precise control of the PF coils currents, confirming the feasibility of implementing the proposed algorithm in real experiments.
Authors
- Xiaobo Zhu
- Panle Liu
- Xinliang Xu (ORCID: https://orcid.org/0000-0002-3342-450X)
- Bo Li (ORCID: https://orcid.org/0000-0001-8895-2054)
- Bin Yang (ORCID: https://orcid.org/0000-0002-2396-6460)
- Jiang Sun
- Yihang Chen
- Xiaoquan Ji
- M.Y. He
- Jiaqi Yang (ORCID: https://orcid.org/0009-0000-6331-9148)
Institutions
- Chengdu University of Technology (CN)
- Southwestern Institute of Physics (CN)
- The Engineering & Technical College of Chengdu University of Technology
Publication Details
- Journal
- Applied Sciences
- Published
- 2025-02-18
- DOI
- https://doi.org/10.3390/app15042175
- Citations
- 1
- Primary Topic
- Magnetic confinement fusion research
- Type
- article
- Field-Weighted Citation Impact
- 1.87
Funders
- National Natural Science Foundation of China