NANAMay 31, 2018

Computational Serendipity and Tensor Product Finite Element Differential Forms

arXiv:1806.000317 citationsh-index: 14
AI Analysis

This work simplifies the implementation of serendipity elements for researchers using finite element methods, addressing a practical bottleneck in computational science.

The paper provides complete lists of computational bases for both trimmed and non-trimmed serendipity finite element families in 2D and 3D, enabling easier adoption and computational efficiency gains by reducing degrees of freedom compared to tensor product elements.

Many conforming finite elements on squares and cubes are elegantly classified into families by the language of finite element exterior calculus and presented in the Periodic Table of the Finite Elements. Use of these elements varies, based principally on the ease or difficulty in finding a "computational basis" of shape functions for element families. The tensor product family, $Q^-_rΛ^k$, is most commonly used because computational basis functions are easy to state and implement. The trimmed and non-trimmed serendipity families, $S^-_rΛ^k$ and $S_rΛ^k$ respectively, are used less frequently because they are newer to the community and, until now, lacked a straightforward technique for computational basis construction. This represents a missed opportunity for computational efficiency as the serendipity elements in general have fewer degrees of freedom than elements of equivalent accuracy from the tensor product family. Accordingly, in pursuit of easy adoption of the serendipity families, we present complete lists of computational bases for both serendipity families, for any order $r\geq 1$ and for any differential form order $0\leq k\leq n$, for problems in dimension $n=2$ or $3$. The bases are defined via shared subspace structures, allowing easy comparison of elements across families. We use and include code in SageMath to find, list, and verify these computational basis functions.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes