English

Subdivision surfaces with isogeometric analysis adapted refinement weights

Numerical Analysis 2018-06-04 v2 Numerical Analysis

Abstract

Subdivision surfaces provide an elegant isogeometric analysis framework for geometric design and analysis of partial differential equations defined on surfaces. They are already a standard in high-end computer animation and graphics and are becoming available in a number of geometric modelling systems for engineering design. The subdivision refinement rules are usually adapted from knot insertion rules for splines. The quadrilateral Catmull-Clark scheme considered in this work is equivalent to cubic B-splines away from extraordinary, or irregular, vertices with other than four adjacent elements. Around extraordinary vertices the surface consists of a nested sequence of smooth spline patches which join C1C^1 continuously at the point itself. As known from geometric design literature, the subdivision weights can be optimised so that the surface quality is improved by minimising short-wavelength surface oscillations around extraordinary vertices. We use the related techniques to determine weights that minimise finite element discretisation errors as measured in the thin-shell energy norm. The optimisation problem is formulated over a characteristic domain and the errors in approximating cup- and saddle-like quadratic shapes obtained from eigenanalysis of the subdivision matrix are minimised. In finite element analysis the optimised subdivision weights for either cup- or saddle-like shapes are chosen depending on the shape of the solution field around an extraordinary vertex. As our computations confirm, the optimised subdivision weights yield a reduction of 50%50\% and more in discretisation errors in the energy and L2L_2 norms. Although, as to be expected, the convergence rates are the same as for the classical Catmull-Clark weights, the convergence constants are improved.

Keywords

Cite

@article{arxiv.1804.05112,
  title  = {Subdivision surfaces with isogeometric analysis adapted refinement weights},
  author = {Qiaoling Zhang and Malcolm Sabin and Fehmi Cirak},
  journal= {arXiv preprint arXiv:1804.05112},
  year   = {2018}
}

Comments

12 pages, 14 figures

R2 v1 2026-06-23T01:23:23.860Z