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High-dimensional finite elements for multiscale Maxwell-type equations

机译:用于多尺度Maxwell型方程的高维有限元

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We consider multiscale Maxwell-type equations in a domain D subset of R-d (d = 2, 3), which depend on n microscopic scales. Using multiscale convergence, we derive the multiscale homogenized problem, which is posed in R(n+1)d. Solving it, we get all the necessary macroscopic and microscopic information. Sparse tensor product finite elements (FEs) are employed, using edge FEs. The method achieves a required level of accuracy with essentially an optimal number of degrees of freedom, which, apart from a multiplying logarithmic term, is equal to that for solving a problem in R-d. Numerical correctors are constructed from the FE solutions. In the two-scale case, an explicit homogenization error is deduced. To get this error, the standard procedure in the homogenization literature requires the solution u(0) of the homogenized problem to belong to H-1(cur1, D). However, in polygonal domains, u(0) belongs only to a weaker regularity space H-s(curl, D) for 0 s 1. We derive a homogenization error estimate for this case. Though we prove the result for two-scale Maxwell-type equations, the approach works verbatim for elliptic and elasticity problems when the solution to the homogenized equation belongs to H1+s(D) (standard procedure requires H-2(D) regularity). This homogenization error estimate is new in the literature. Thus, for two-scale problems, an explicit error for the numerical corrector is obtained; it is of the order of the sum of the homogenization error and the FE error. For the case of more than two scales, we construct a numerical corrector, albeit without a rate of convergence, as such a homogenization error is not available. Numerical experiments confirm the theoretical results.
机译:我们考虑在R-D(D = 2,3)的域D子集中的MultiScale Maxwell型方程,这取决于N微观尺度。使用多尺度融合,我们得出了多尺度均质问题,其在R(n + 1)d中提出。解决它,我们得到所有必要的宏观和微观信息。使用边缘FES使用稀疏的张量产品有限元(FES)。该方法实现了所需的精度水平,其基本上是最佳的自由度,除了乘法对数项之外,该方法等于解决R-D中的问题。数值校正器由FE解决方案构建。在双模案例中,推导出明确的均化误差。为了获得此错误,均质化文献中的标准过程要求均质问题的溶液U(0)属于H-1(Cur1,D)。然而,在多边形域中,U(0)仅属于较弱的规则性空间H-S(卷曲,D),用于0& s& 1.我们为这种情况推出了均质错误估计。虽然我们证明了两种尺度麦克斯韦型方程的结果,但是当均质方程的解决方案属于H1 + S(D)时,该方法逐字用于椭圆形和弹性问题(标准程序需要H-2(D)规则) 。这种均质误差估计是文献中的新功能。因此,对于两个尺度问题,获得了数值校正器的显式误差;它是均质错误误差和FE错误的总和的顺序。对于两个以上的尺度的情况,我们构造了一个数字校正器,尽管没有收敛速率,因此不可用。数值实验证实了理论结果。

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