Date Thesis Awarded

5-2024

Access Type

Honors Thesis -- Access Restricted On-Campus Only

Degree Name

Bachelors of Science (BS)

Department

Physics

Advisor

Saskia Mordijck

Committee Members

Eugeniy Mikhailov

Heather Sasinowska

Abstract

Non-ionized neutral particles play a key role in the function of fusion reactors, in particular with regards to tokamak fueling and performance; however, in the future, higher plasma densities could potentially limit their ability to enter the system before ionizing, negatively impacting the reactors’ overall efficacy. For this reason, it is important to have reliable methods of predicting neutral behavior within tokamaks. This thesis has seen the translation of one such tool, KN1D, from its original programming language into Python. The newly-written code, KN1DPy, has been tested against outputs from the original to verify the accuracy of its models. The results from these trials have shown that, while KN1DPy is able capture some of the large-scale trends that are to be expected from neutral densities, specific predictions are not yet possible as further verification is necessary relating to ionization rates and boundary pressure conditions. An additional goal of this project has been updating the reaction rate coefficients used within KN1DPy to take advantage of the online ADAS database. Testing the code using these ADAS rates against the originals has shown good agreement between results, with less than 2.2% difference in output neutral densities. This successful integration indicates that the included ADAS rates are indeed a viable replacement for the old, hard-coded values used originally.

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