Nonlinear gyrokinetic predictions of SPARC burning plasma profiles enabled by surrogate modeling

Multi-channel, nonlinear predictions of core temperature and density profiles are performed for the SPARC tokamak accounting for both kinetic neoclassical and fully nonlinear gyro-kinetic turbulent fluxes. A series of flux-tube, nonlinear, electromagnetic simulations using the CGYRO code with six gyrokinetic species are coupled to a nonlinear optimizer using Gaussian Process regression techniques. The simultaneous evolution of energy sources, including alpha heat, radiation, and energy exchange, coupled with these high fidelity models and techniques, leads to a converged solution in electron temperature, ion temperature and electron density channels with a minimal number of expensive gyrokinetic simulations without compromising accuracy本研究针对SPARC托卡马克（tokamak）开展多通道芯部温度与密度分布的非线性预测，同时考量动理学新经典效应与全非线性回旋动理学湍流通量（fully nonlinear gyro-kinetic turbulent fluxes）的影响。采用CGYRO代码开展的一系列包含六类回旋动理学粒子（gyrokinetic species）的通量管非线性电磁模拟，与基于高斯过程回归（Gaussian Process regression）技术的非线性优化器相耦合。将阿尔法加热（alpha heat）、辐射与能量交换等能量源的同步演化过程，与上述高保真模型及技术相结合，可在不牺牲精度的前提下，以极少的高成本回旋动理学模拟（gyrokinetic simulations）运行次数，获得电子温度、离子温度与电子密度通道的收敛解。