Quasilinear Gyrokinetic Modeling of Reduced Transport in the Presence of High Impurity Content, Large Gradients, and Large Geometric α

Pellet-fueled tokamak discharges lead to large gradients that can destabilize electrostatic microinstabilities, thereby driving anomalous turbulent transport [1]. However, large gradients can also lead to large geometric α, a stabilizing parameter in certain regimes [2]. The resulting transport is inherently constrained to be ambipolar; in effect, these large gradients can make this flux constraint impossible to satisfy, resulting in stabilization and the reduction of turbulent transport [3]. Due to the high computational cost of nonlinear gyrokinetic simulations, using a reduced turbulent transport model is ideal for predictive modeling. We test the extent to which the gyrokinetic quasilinear code QuaLiKiz [4] can reliably predict anomalous transport in pellet-fueled discharge regimes to determine parameters that lead to turbulent transport reduction. We use the gyrokinetic code GENE [5], based on first principles, as a point of comparison for QuaLiKiz. Unlike GENE, QuaLiKiz uses many approximations to ensure computational tractability. In particular, QuaLiKiz assumes a Gaussian eigenfunction, uses s-α geometry, and only captures electrostatic fluctuations. We test, and in some cases, relax these approximations to ensure accurate predictions in pellet-fueled discharge scenarios.