In this paper we introduce an algorithm based on a sparse grid adaptive refinement, for the approximation of the eigensolutions to parametric problems arising from elliptic partial differential equations. In particular, we are interested in detecting the crossing of the hypersurfaces describing the eigenvalues as a function of the parameters. The a priori matching is followed by an a posteriori verification, driven by a suitably defined error indicator. At a given refinement level, a sparse grid approach is adopted for the construction of the grid of the next level, by using the marking given by the a posteriori indicator. Various numerical tests confirm the good performance of the scheme.
翻译:在本文中,我们引入了一种基于稀疏的网格适应性改进的算法,以近似于因椭圆部分差分方程产生的参数问题,特别是,我们有兴趣探测高表层的跨度,将egenvalue描述为参数的函数。先验匹配后由适当界定的误差指标驱动进行后验。在某种细化水平上,采用稀疏的网格方法,利用后验指标的标记来构建下一层次的网格。各种数字测试证实了这一办法的良好性能。