NANAJun 10, 2017

Construction of analysis-suitable $G^1$ planar multi-patch parameterizations

arXiv:1706.0326487 citations
Originality Incremental advance
AI Analysis

This work addresses the need for suitable multi-patch parameterizations in isogeometric analysis to achieve optimal approximation properties for C1-smooth functions.

The paper presents a method to construct analysis-suitable G1 multi-patch parameterizations for planar domains, ensuring optimal convergence of C1 isogeometric spaces. Numerical tests show optimal convergence under mesh refinement, whereas generic parameterizations lead to severely reduced convergence order.

Isogeometric analysis allows to define shape functions of global $C^{1}$ continuity (or of higher continuity) over multi-patch geometries. The construction of such $C^{1}$-smooth isogeometric functions is a non-trivial task and requires particular multi-patch parameterizations, so-called analysis-suitable $G^{1}$ (in short, AS-$G^{1}$) parameterizations, to ensure that the resulting $C^{1}$ isogeometric spaces possess optimal approximation properties, cf. [7]. In this work, we show through examples that it is possible to construct AS-$G^{1}$ multi-patch parameterizations of planar domains, given their boundary. More precisely, given a generic multi-patch geometry, we generate an AS-$G^{1}$ multi-patch parameterization possessing the same boundary, the same vertices and the same first derivatives at the vertices, and which is as close as possible to this initial geometry. Our algorithm is based on a quadratic optimization problem with linear side constraints. Numerical tests also confirm that $C^{1}$ isogeometric spaces over AS-$G^{1}$ multi-patch parameterized domains converge optimally under mesh refinement, while for generic parameterizations the convergence order is severely reduced.

Foundations

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

Your Notes