We consider nodal-based Lagrangian interpolations for the finite element approximation of the Maxwell eigenvalue problem. The first approach introduced is a standard Galerkin method on Powell-Sabin meshes, which has recently been shown to yield convergent approximations in two dimensions, whereas the other two are stabilized formulations that can be motivated by a variational multiscale approach. For the latter, a mixed formulation equivalent to the original problem is used, in which the operator has a saddle point structure. The Lagrange multiplier introduced to enforce the divergence constraint vanishes in an appropriate functional setting. The first stabilized method we consider consists of an augmented formulation with the introduction of a mesh dependent term that can be regarded as the Laplacian of the multiplier of the divergence constraint. The second formulation is based on orthogonal projections, which can be recast as a residual based stabilization technique. We rely on the classical spectral theory to analyze the approximating methods for the eigenproblem. The stability and convergence aspects are inherited from the associated source problems. We investigate the numerical performance of the proposed formulations and provide some convergence results validating the theoretical ones for several benchmark tests, including ones with smooth and singular solutions.
翻译:我们考虑基于节点的Lagrangian插值来有限元逼近Maxwell特征值问题。首先介绍了一种在Powell-Sabin网格上的标准Galerkin方法,最近已经证明在二维情况下可以产生收敛的逼近解决方案,另外两种则是可以通过一个变分多尺度方法来获得的稳定公式。对于后者,采用了一个等价于原始问题的混合公式,其算子具有鞍点结构。为实现散度约束,引入了拉格朗日乘数,该乘数在适当的函数空间中为零。我们考虑引入依赖于网格的项来稳定第一种方法,该项可视为散度约束的拉格朗日乘数的Laplacian。第二种方法则基于正交投影,可被重构为基于残差的稳定技术。我们依赖经典的谱理论来分析本文所提出的逼近特征值问题的方法。稳定性和收敛性的方面可由相关源问题继承。我们对所提出的公式进行了数值性能研究,并针对包括平滑和奇异解在内的多个基准测试提供了一些收敛性结果的验证。