Transport model validation in support of burning plasma physics

Improving confidence in the predictions for performance in burning plasmas is of great importance for accelerating the development of fusion energy. State-of-the-art predictions of pressure profiles and rotation profiles in standard aspect ratio tokamaks like ITER and SPARC, as well as spherical tokamaks, are performed using physics-based, but reduced, models of turbulent transport. The details of the turbulence can be simulated in burning plasmas using high-fidelity nonlinear gyrokinetic simulation. Confidence in reduced models and in predictions from nonlinear gyrokinetic simulation relies on rigorous validation against experimental measurements. Validation studies carried out on major tokamak facilities around the world are driven by steady investment aimed at advancing the frontiers of plasma diagnostics, data analysis techniques, plasma theory, and computational science. This talk will summarize research carried out at the MIT PSFC on transport model validation in support of burning plasma physics, including new diagnostic development, fluctuation measurement databases, and integrated modeling approaches that leverage AI and machine learning. O. Meneghini et al. 2021 Nucl. Fusion 61 026006; C. Chrystal et al 2020 Nucl. Fusion 60 036003; P. Rodriguez-Fernandez et al., J. Plasma Phys. 86, 865860503 (2020); B. Patel, et al. 46th EPS Conference on Plasma Physics, EPS 2019; G. Staebler et al. 2017. Nucl. Fusion 57 (6), 066046; N. Howard et al. Physics of Plasmas 28, 072502 (2021).