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Jacobi-Davidson iteration based reduced order finite element models for radar cross-section

机译:基于Jacobi-Davidson迭代的雷达截面降阶有限元模型

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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.
机译:雷达横截面(RCS)等大规模散射问题的有限元建模导致大矩阵。使用涉及平面波激励的这些模型的Eigenspace投影的模型顺序(Mor)需要解决非线性特征值问题。本文提出了一种有利地计算宽带RC的方法。 jacobi-davidson迭代用于生成投影空间。在系统规模中减少了许多订单,并举例说明计算成本。

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