H2 regularity properties of singular parameterizations in isogeometric analysis

  • Authors:

  • T. Takacs;B. JüTtler

  • Affiliations:

  • Institute of Applied Geometry, Johannes Kepler University, Faculty of Natural Sciences and Engineering, Altenberger Straíe 69, 4040 Linz, Austria;Institute of Applied Geometry, Johannes Kepler University, Faculty of Natural Sciences and Engineering, Altenberger Straíe 69, 4040 Linz, Austria

  • Venue:
  • Graphical Models
  • Year:
  • 2012

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Abstract

Isogeometric analysis (IGA) is a numerical simulation method which is directly based on the NURBS-based representation of CAD models. It exploits the tensor-product structure of 2- or 3-dimensional NURBS objects to parameterize the physical domain. Hence the physical domain is parameterized with respect to a rectangle or to a cube. Consequently, singularly parameterized NURBS surfaces and NURBS volumes are needed in order to represent non-quadrangular or non-hexahedral domains without splitting, thereby producing a very compact and convenient representation. The Galerkin projection introduces finite-dimensional spaces of test functions in the weak formulation of partial differential equations. In particular, the test functions used in isogeometric analysis are obtained by composing the inverse of the domain parameterization with the NURBS basis functions. In the case of singular parameterizations, however, some of the resulting test functions do not necessarily fulfill the required regularity properties. Consequently, numerical methods for the solution of partial differential equations cannot be applied properly. We discuss the regularity properties of the test functions. For one- and two-dimensional domains we consider several important classes of singularities of NURBS parameterizations. For specific cases we derive additional conditions which guarantee the regularity of the test functions. In addition we present a modification scheme for the discretized function space in case of insufficient regularity. It is also shown how these results can be applied for computational domains in higher dimensions that can be parameterized via sweeping.