Computational engineering and numerical simulations are essential in designing and analyzing accelerator magnets, especially as magnet geometries become more complex. During the early design phase, engineers often need to explore multiple magnet designs quickly for rough quality estimates. However, modeling each design in a sophisticated CAD software can be time-consuming and inefficient, as many ideas will not make it past the initial phase.

This proposal aims to accelerate the process by leveraging image recognition. You will develop a Python package that can interpret hand-drawn, 2D magnet geometries– recognizing the iron yoke shape and coil wire positions – and convert them into a format compatible with our in-house Biot-Savart-based solver [1] for magnetic field simulations.