Learning electromagnetic fields based on finite element basis functions

📝 Original Info

• Title: Learning electromagnetic fields based on finite element basis functions
• ArXiv ID: 2507.19255
• Date: 2025-07-25
• Authors: 제공된 정보에 저자 목록이 포함되어 있지 않습니다.

📝 Abstract

Parametric surrogate models of electric machines are widely used for efficient design optimization and operational monitoring. Addressing geometry variations, spline-based computer-aided design representations play a pivotal role. In this study, we propose a novel approach that combines isogeometric analysis, proper orthogonal decomposition and deep learning to enable rapid and physically consistent predictions by directly learning spline basis coefficients. The effectiveness of this method is demonstrated using a parametric nonlinear magnetostatic model of a permanent magnet synchronous machine.

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