David R. White

Automatic scheme selection for toolkit hex meshing

Current hexahedral mesh generation techniques rely on a set of meshing tools, which when combined with geometry decomposition leads to an adequate mesh generation process. Of these tools, sweeping tends to be the workhorse algorithm, accounting for at least 50% of most meshing applications. Constraints which must be met for a volume to be sweepable are derived, and it is proven that these constraints are necessary but not sufficient conditions for sweepability. This paper also describes a new algorithm for detecting extruded or sweepable geometries. This algorithm, based on these constraints, uses topological and local geometric information, and is more robust than feature recognition-based algorithms. A method for computing sweep dependencies in volume assemblies is also given. The auto sweep detect and sweep grouping algorithms have been used to reduce interactive user time required to generate all-hexahedral meshes by filtering out non-sweepable volumes needing further decomposition and by allowing concurrent meshing of independent sweep groups. Parts of the auto sweep detect algorithm have also been used to identify independent sweep paths, for use in volume-based interval assignment.

Automated Hexahedral Mesh Generation by Generalized Multiple Source to Multiple Target Sweeping

This paper presents an enhanced sweeping mesh generation algorithm. Traditional sweeping techniques create all hexahedral element meshes by projecting an existing single-surface mesh along a specified trajectory to a specified single target surface. The work reported here enhances the traditional method by creating all hexahedral element meshes between multiple source surfaces and multiple target surfaces. The new algorithm is based on an innovated application of Boolean operations. The core of this process is the rebuilding of the boundary representations of source surfaces by Boolean operations between the boundary loops of both target and source to incorporate a virtual geometry decomposition. Published in 2000 by John Wiley & Sons, Ltd.

CCSweep: automatic decomposition of multi-sweep volumes

CCSweep is a new method to automatically decompose multi-sweepable volumes into many-to-one sweepable volumes. Multi-sweepable volumes contain both multiple source and multiple target faces. In hexahedral mesh generation, most sweeping techniques handle many-to-one sweepable volumes that contain multiple source faces, but they are limited to volumes with only a single target face. Recent proposals to solve the multi-sweep problem have several disadvantages, including: indeterminate edge sizing or interval matching constraints, over-dependence on input mesh discretization, loop Boolean restrictions on creating only loops with even numbers of nodes, and unstable loop imprinting when interior holes exist. These problems are overcome through CCSweep. CCSweep decomposes multi-sweep volumes into many-to-one sweepable sub-volumes by projecting the target faces through the volume onto corresponding source faces. The projected faces are imprinted with the source faces to determine the decomposition of the solid. Interior faces are created to decompose the volume into separate new volumes. The new volumes have only single target faces and are represented in the meshing system as real, solid geometry, enabling them to be automatically meshed using existing many-to-one hexahedral sweeping approaches. The results of successful application of CCSweep to a number of problems are shown in this paper.

Meshing complexity: predicting meshing difficulty for single part CAD models

This paper proposes a method for predicting the complexity of meshing computer aided design (CAD) geometries with unstructured, hexahedral, finite elements. Meshing complexity refers to the relative level of effort required to generate a valid finite element mesh on a given CAD geometry. A function is proposed to approximate the meshing complexity for single part CAD models. The function is dependent on a user defined element size as well as on data extracted from the geometry and topology of the CAD part. Several geometry and topology measures are proposed, which both characterize the shape of the CAD part and detect configurations that complicate mesh generation. Based on a test suite of CAD models, the function is demonstrated to be accurate within a certain range of error. The solution proposed here is intended to provide managers and users of meshing software a method of predicting the difficulty in meshing a CAD model. This will enable them to make decisions about model simplification and analysis approaches prior to mesh generation.