Adaptive Subdomain Model Order Reduction With Discrete Empirical Interpolation Method for Nonlinear Magneto-Quasi-Static Problems

被引：18

作者：

Sato, Yuki ^{[1
,2
]}

Clemens, Markus ^{[3
]}

Igarashi, Hajime ^{[1
]}

机构：

[1] Hokkaido Univ, Grad Sch Informat Sci & Technol, Sapporo, Hokkaido 0600814, Japan

[2] Japan Soc Promot Sci, Tokyo 1020083, Japan

[3] Berg Univ Wuppertal, Chair Electromagnet Theory, Fachbereich 9, D-42119 Wuppertal, Germany

来源：

IEEE TRANSACTIONS ON MAGNETICS | 2016年 / 52卷 / 03期

关键词：

Finite element method (FEM); magneto-quasi-static (MQS) field; model order reduction (MOR); nonlinear problem; FIELD SIMULATIONS;

D O I：

10.1109/TMAG.2015.2489264

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a novel adaptive subdomain model order reduction (MOR) based on proper orthogonal decomposition (POD) and discrete empirical interpolation (DEI) methods for nonlinear magneto-quasi-static (MQS) problems. In this method, a nonlinear region is decomposed into two regions, where one of the regions includes all those finite elements that have a particularly strong saturation and the other region does not. MOR based on POD and DEI methods is applied only to the latter region. Both the regions are determined automatically at each time step. It is shown that this method can effectively reduce the computational time to solve the nonlinear MQS problems without losing the quality of accuracy.

引用

页数：4

共 34 条

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