电磁系统非线性有限元近似中模型维数的降维

S. Rutenkroger, B. Deken, S. Pekarek
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引用次数: 10

摘要

提出了一种降低电磁元件有限元模型阶数的方法。在提出的技术中,利用经验特征向量(EE)将全阶有限元模型转换为用户指定(或误差确定)的降阶系统。EE方法使用对完整模型的响应的观察来构建复制完整系统的简化基。由饱和引起的非线性属性在简化中自然保留,同时大大减少了对组件建模所需的数值努力。应用EE方法对铁芯环形电感进行了建模。对于线性、固定时间步长分析,计算速度提高了4倍,对于非线性、可变时间步长分析,计算速度提高了71倍,而精度没有明显的损失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reduction of model dimension in nonlinear finite element approximations of electromagnetic systems
A method to reduce the order of finite element (FE) based models of electromagnetic components is presented. In the technique proposed, a full order FE model is transformed into a user specified (or error determined) reduced order system using empirical eigenvectors (EE). The EE method uses an observation of the response of a full model to construct a reduced basis that replicates a full system. Nonlinear attributes resulting from saturation are naturally preserved in the reduction, while the numerical effort required to model the component is greatly reduced. The EE method has been applied to model an iron-core toroidal inductor. A four-fold increase in the speed of computation has been obtained for a linear, fixed time step analysis and a seventy-one fold increase for a nonlinear, variable time step analysis, without observable loss in accuracy.
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