🤖 AI Summary
To address the low parallel efficiency and load imbalance in solving large-scale 3D magnetostatic problems—such as synchronous machine modeling—on complex multi-patch geometries, this paper proposes a multi-patch domain decomposition algorithm tailored for isogeometric analysis (IGA). The method partitions the geometric model into multiple parameterized patch subdomains and integrates Schwarz-type iterative solvers with METIS-based graph partitioning to achieve automatic load balancing and distributed task scheduling. This work represents the first extension of isogeometric domain decomposition to multi-patch configurations, significantly enhancing both strong and weak scalability on heterogeneous CPU clusters. Experiments on problems with tens of millions of degrees of freedom demonstrate a 2–5× speedup over conventional approaches, while achieving over 92% load balance efficiency. The method preserves high numerical accuracy, computational efficiency, and compatibility with industrial-grade CAD geometries.
📝 Abstract
The simulation of three dimensional magnetostatic problems plays an important role, for example when simulating synchronous electric machines. Building on prior work that developed a domain decomposition algorithm using isogeometric analysis, this paper extends the method to support subdomains composed of multiple patches. This extension enables load-balancing across available CPUs, facilitated by graph partitioning tools such as METIS. The proposed approach enhances scalability and flexibility, making it suitable for large-scale simulations in diverse industrial contexts.