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Error Estimation for Model-Order Reduction of Finite-Element Parametric Problems

机译:有限元参数问题模型降阶的误差估计

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摘要

To solve a parametric model in computational electromagnetics, the finite-element (FE) method is often used. To reduce the computational time and the memory requirement, the FE method can be combined with the model-order reduction technique like the proper orthogonal decomposition and (discrete) empirical interpolation methods. These three numerical methods introduce the errors of discretization, reduction, and interpolation, respectively. The solution of the parametric model will be efficient if the three errors are of the same order and so they need to be evaluated and compared. In this paper, we propose an a posteriori error estimator based on the verification of the constitutive law, which estimates the three different errors. An example of application in magnetostatics with 11 parameters is treated where it is shown how the error estimator can be used to control and to improve the accuracy of the solution of the reduced model.
机译:为了求解计算电磁学中的参数模型,经常使用有限元(FE)方法。为了减少计算时间和内存需求,可以将有限元方法与模型级约简技术相结合,例如适当的正交分解和(离散)经验插值方法。这三种数值方法分别引入了离散化,归约化和内插化的误差。如果三个误差的阶次相同,则参数模型的解决方案将非常有效,因此需要对其进行评估和比较。在本文中,我们基于本构律的验证提出了一种后验误差估计器,该估计器估计了三个不同的误差。讨论了一个具有11个参数的静磁应用示例,该示例显示了如何使用误差估计器来控制和提高简化模型求解的精度。

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