Optimizing a magnetic equilibrium reverse solver for SPARC
Description: The SPARC project aims to demonstrate net fusion energy on an accelerated timescale. A dedicated team of over 100 people are all working together to make this dream a reality! In order to recreate the reaction that power the stars, SPARC relies on strong magnetic fields to confine a ring of plasma that is hotter than the center of the sun. The SPARC team is currently focused on developing powerful electromagnets that can get the job done and part of this is determining the coil currents required. Thus far, an open source code called FreeGS (https://github.com/bendudson/freegs) has been used to perform this scoping study, however the tool is limited in its capabilities. The project will focus on making the solver more user-friendly for future scenario development, which can be through a number of mechanisms: developing a means to better constrain the problem; applying statistical inference tools; and/or algorithms that can improve solver convergence. This project is ideal for learning the basics of fusion energy and tokamak design.
Desired skills: • A working knowledge of electricity and magnetism
• Strong coding background in python
• Strong mathematics background in particular with solving non-linear systems of partial differential equations
• Statistical inference and machine learning (optional)
Research supervisor: Adam Q Kuang, email@example.com
Faculty sponsor: Zach Hartwig, firstname.lastname@example.org