基于Jacobi-Davidson迭代的雷达截面降阶有限元模型

N. Kumar, K. Vinoy, S. Gopalakrishnan
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引用次数: 0

摘要

像雷达横截面(RCS)这样的大尺度散射问题的有限元建模需要很大的矩阵。利用平面波激励下这些模型的特征空间投影进行模型降阶需要解决非线性特征值问题。本文提出了一种方便计算宽带RCS的方法。采用Jacobi-Davidson迭代生成投影空间。举例说明了系统尺寸和计算成本降低了许多个数量级。
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Jacobi-Davidson iteration based reduced order finite element models for radar cross-section
Finite element modeling of large-scale scattering problems like radar cross-section (RCS) lead to large matrices. Model order reduction (MOR) using eigenspace projection of these models involving plane wave excitation requires solution of nonlinear eigenvalue problems. This paper proposes a methodology to expediently compute wideband RCS. Jacobi-Davidson iteration is used to generate the projection spaces. Reduction by many orders in the system size and the computational cost is exemplified.
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