Prediction of Performance and Turbulence in ITER Burning Plasmas via Nonlinear Gyrokinetic Profile Prediction (2404.17040v1)

Abstract: Burning plasma performance, transport, and the effect of hydrogen isotope on confinement has been predicted for ITER baseline scenario (IBS) conditions using nonlinear gyrokinetic profile predictions. Accelerated by surrogate modeling [P. Rodriguez-Fernandez NF 2022], high fidelity, nonlinear gyrokinetic simulations performed with the CGYRO code [J. Candy JCP 2016], were used to predict profiles of Ti, Te, and ne while including the effects of alpha heating, auxiliary power, collisional energy exchange, and radiation losses. Predicted profiles and resulting energy confinement are found to produce fusion power and gain that are approximately consistent with mission goals (Pfusion = 500MW at Q=10) for the baseline scenario and exhibit energy confinement that is within 1 sigma of the H-mode energy confinement scaling. The power of the surrogate modeling technique is demonstrated through the prediction of alternative ITER scenarios with reduced computational cost. These scenarios include conditions with maximized fusion gain and an investigation of potential Resonant Magnetic Perturbation effects on performance with a minimal number of gyrokinetic profile iterations required. These predictions highlight the stiff ITG nature of the core turbulence predicted in the ITER baseline and demonstrate that Q>17 conditions may be accessible by reducing auxiliary input power while operating in IBS conditions. Prediction of full kinetic profiles allowed for the projection of hydrogen isotope effects around ITER baseline conditions. The gyrokinetic fuel ion species was varied from H, D, and 50/50 D-T and kinetic profiles were predicted. Results indicate that a weak or negligible isotope effect will be observed to arise from core turbulence in ITER baseline scenario conditions. The resulting energy confinement, turbulence, and density peaking, and the implications for ITER operations will be discussed.