Verification of KN1DPy for Improved Modelling of Neutral Densities in Tokamaks

Tokamaks are a concept which have shown promise for generating fusion energy and work by confining high-temperature plasmas within a magnetic field. The fusion gain, and thus performance of the tokamak concept, is strongly linked to the plasma density and our ability to fuel the plasma using gas, also referred to as neutrals [1]. However, while finding neutral distribution functions will be an important task in the design of future devices, measurements and validated modeling of fueling have only recently risen to prominence. KN1D solves the atomic and molecular hydrogen distribution functions satisfying the Boltzmann equation, while also simulating the effects of charge exchange collisions, ionization and dissociation, and elastic collisions for a given electron density and temperature profile [2]. The original code was developed by B. LaBombard using a combination of IDL and Fortran. A newly developed version of KN1D written in Python, KN1DPy, will be compared to the original and validated against experimental data from the C-Mod Tokamak. These comparisons will help guide future development focused on improving the atomic physics models, or expanding the model from 1D(radial)+2D-velocity space, to 2D(radial, poloidal)+3D-velocity space. Other potential improvements include linking KN1DPy’s reaction coefficients to open-source databases for comparison against using the existing rates, and expanding the code to include additional atomic and molecular reactions.



[1] S. Mordijck, Nucl. Fusion 60, 082006 (2020)

[2] LaBombard B., KN1D: A 1-D Space, 2-D Velocity, Kinetic transport algorithm for atomic and molecular hydrogen in an ionizing plasma, MIT Plasma Science and Fusion Center Report PSFC/RR-01-3; Research Report PSFC/RR-01-3