This work introduces a novel, fully robust and highly-scalable, $h$-adaptive aggregated unfitted finite element method for large-scale interface elliptic problems. The new method is based on a recent distributed-memory implementation of the aggregated finite element method atop a highly-scalable Cartesian forest-of-trees mesh engine. It follows the classical approach of weakly coupling nonmatching discretisations at the interface to model internal discontinuities at the interface. We propose a natural extension of a single-domain parallel cell aggregation scheme to problems with a finite number of interfaces; it straightforwardly leads to aggregated finite element spaces that have the structure of a Cartesian product. We demonstrate, through standard numerical analysis and exhaustive numerical experimentation on several complex Poisson and linear elasticity benchmarks, that the new technique enjoys the following properties: well-posedness, robustness with respect to cut location and material contrast, optimal ($h$-adaptive) approximation properties, high scalability and easy implementation in large-scale finite element codes. As a result, the method offers great potential as a useful finite element solver for large-scale interface problems modelled by partial differential equations.
翻译:这项工作引入了一种新颖的、完全稳健的和高度可扩展的、以美元为单位的、适应性强的、适用于大比例界面椭圆形问题综合不适的固定要素方法。新方法基于最近对可高度缩放的Cartesian Forest-forest-frees网状引擎采用的综合有限要素方法的分布式模拟实施。它遵循了在界面界面上将不匹配的离异性弱结合到模拟界面的内部不一致性的典型方法。我们建议将单位平行单元格组合计划自然延伸至与有限界面的问题;它直接导致具有卡尔提斯产品结构的有限要素空间的汇总。我们通过对若干复杂的Poisson和线性弹性基准进行标准数字分析和详尽无遗的量化实验,表明该新技术具有以下特性:准确性、在缩小位置和材料对比方面坚固性强、最佳($-可调)近效性准性、高度可伸缩性、在大规模定质要素代码中易于执行。因此,该方法提供了巨大的潜力,作为大尺度的模型化的定质要素方程式,按大比例方程式解决问题。