An Expanded Python Version of KN1D for Modeling the Neutral Densities of SPARC

In fusion research, predicting neutral profiles is critical to understand the fueling requirements for a fusion reactor [1]. KN1D [2], developed in the ‘90s, relies on a collisional-radiative model for the 10 most important electron interactions [3], and elastic collisions are included using a BGK model [4] instead of using modern open-source databases of atomic physics reactions [5]. We will first convert KN1D into Python to simplify its use for the wider community and improve compatibility with experimental data as well as predictive modeling.

The updated code will be verified through comparison to the previous IDL version using data from the C-Mod tokamak at MIT. Using the newly developed KN1DPy, we will perform predictive analysis of neutral densities for the SPARC fusion device. 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 [6][7]. However, there is a lack of adequate modeling of neutral profiles. With the development of KN1D, we hope to produce models for neutral densities to inform us further about electron densities and pressure gradients.

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2. B. LaBombard, MIT Plasma Science and Fusion Center Report PSFC/RR-01-3; Research Report PSFC/RR-01-3

3. K. Sawada and T.Fujimoto, J. Appl. Phys. 78.5 (1995): 2913-2924.

4. P. L. Bhatnagar, E. P. Gross and M. Krook, Phys. Rev. 94.3 (1954): 511.

5. H. P. Summers, et al. AIP Conference Proceedings. Vol. 901. No. 1. American Institute of Physics, 2007.

6. A.J. Creely, et al., J. of Plasma Phys. 86, 865860502 (2020).

7. M. Greenwald, J.of Plasma Phys. 86, 861860501 (2020).