no code implementations • 8 Feb 2022 • Andrés Beltrán-Pulido, Ilias Bilionis, Dionysios Aliprantis
The objective of this paper is to investigate the ability of physics-informed neural networks to learn the magnetic field response as a function of design parameters in the context of a two-dimensional (2-D) magnetostatic problem.
