Underlying Physics of TAE-induced ITG Suppression and associated Zonal Flows
2025 Research Campaign, Thrust: Fast Ions, Turbulence and Alfven Waves
Purpose of Experiment
As the world fusion program approaches the era of burning plasmas, the traditional segmentation of topics—such as “transport” and “energetic particles”—is being reshaped. In a burning plasma, distinguishing between energetic particle confinement and the instabilities governing them (hereafter referred to as AE modes) becomes impractical. The interplay between energetic particles and high-frequency AEs, as well as thermal particles and low-frequency drift waves, results in significant cross-scale coupling. A crucial mechanism for this interaction is the emergence of zonal modes, which encompass flow, fields, and corrugations. Both AE and drift wave interactions can drive zonal modes, creating feedback loops that affect both processes. Therefore, confinement physics must adapt to this new paradigm of interconnected feedback. In FY2024, two experiments focusing on energetic particles and turbulence confirm that toroidal Alfvén eigenmodes (TAEs) can effectively mitigate ion temperature gradient (ITG) instabilities. Multi-TAE interactions can fully suppress ITG, leading to enhanced thermal plasma confinement. Notably, the impact of TAEs on ITG is significantly greater than that of mean flow or dilution effects. Preliminary data hint at an increase in fluctuations of axis-symmetric flow. This follow-up experiment aims to delve deeper into the physics of turbulence suppression and confinement improvement. It will also focus on the development of a controllable experimental actuator to extend periods of enhanced confinement, ultimately enhancing plasma performance in advanced scenarios. The DIII-D facility contributes crucial resources to this study, including advanced diagnostics for fluctuations and energetic particles. The BES and DBS systems facilitate measurements of TAE, ITG and zonal flows, while the FIDA, INPA, and IFIDA systems measure fast ion distributions—essential for model comparisons. These diagnostic systems are essential to understand the physics behind.