Modeling the Neutral Densities of SPARC using Python Version of KN1D

In current-day tokamaks, neutral ionization has played a significant role in fueling, but we lack accurate information about neutral density profiles [1]. In future devices, however, including SPARC, the plasma will be more opaque to neutrals, limiting the neutral penetration past the separatrix. Therefore, affecting the plasma density profile. To model the influence of neutral fueling, we use KN1D, Kinetic Neutral 1-D, a kinetic transport algorithm for atomic and molecular hydrogen in an ionizing plasma [2]. The program determines the neutral atomic and molecular hydrogen distribution functions, f_n and f_H2 respectively. This is accomplished via electron impact reactions, the energy equilibrium model, elastic collisions using a BGK model, and molecular charge exchange [2].

Originally KN1D was developed in the 2000s and written in IDL, making it difficult to implement in modern-day programs. As a result, we have developed an initial draft of a Python version of KN1D, titled KN1DPy. Currently, the SPARC team uses code to produce models for ICRH heating, turbulent transport, pedestal structure, edge profiles, magnetohydrodynamics (MHD) stability, and ripple loss of fast alphas [3]. However, there is a lack of adequate modeling of neutral profiles. With the development of KN1D, we hope to produce models for neutral densities which can further inform us about electron densities and pressure gradients.

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

3. A. J. Creely et al. J. Plasma Phys. vol. 86, 865860502 (2020)