Date Thesis Awarded

5-2024

Access Type

Honors Thesis -- Open Access

Degree Name

Bachelors of Science (BS)

Department

Physics

Advisor

Saskia Mordijck

Committee Members

Marc Sher

Leah Shaw

Abstract

Currently, neutral recycling is a crucial contributor to fueling the plasma within tokamaks. However, Commonwealth Fusion System’s SPARC Tokamak is expected to be more opaque to neutrals. Thus, we anticipate that the role of neutral recycling in fueling will decrease. Since SPARC is predicted to have a groundbreaking fusion power gain ratio of Q ≈ 10, we must have a concrete understanding of the opacity
and whether or not alternative fueling practices must be included. To develop said understanding, we produced neutral density profiles via KN1DPy, a 1D kinetic neutral transport code for atomic and molecular hydrogen in an ionizing plasma. KN1DPy
is a one-to-one recode of the IDL program KN1D, originally developed in the early 2000s. We translated KN1D from IDL to Python to increase accessibility and allow for better coupling with other modern programs. We verified KN1DPy using Alcator C-Mod data and comparing the Python and the IDL outputs. Using simulated profiles for electron density (n_e), ion temperature (T_i), and electron temperature (T_e), we can run KN1DPy and produce simulated neutral density profiles for SPARC. These results can then be compared to the expectation from the empirical equation for opacity, which states that most neutrals will ionize before crossing the separatrix.
Results consistent with these expectations will mean that neutral recycling plays a weaker role in fueling the plasma core.

Recommended Citation

Galleher, Gwendolyn R., "Modeling the Neutral Densities of SPARC Using a Python Version of KN1D" (2024). Undergraduate Honors Theses. William & Mary. Paper 2225.
https://scholarworks.wm.edu/honorstheses/2225