Nonlinear gyrokinetic predictions of SPARC burning plasma profiles enabled by surrogate modeling
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https://doi.org/10.7910/DVN/2BKB3O
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资源简介:
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
创建时间:
2022-05-09



