Marcum, David L.

Committee Member

Luke, Edward A.

Committee Member

Lim, Hyeona

Committee Member

Remotigue, Michael G.

Date of Degree


Document Type

Dissertation - Open Access


Computational Engineering (Program)

Degree Name

Doctor of Philosophy


College of Engineering


Computer Aided Design (CAD) models often need to be processed due to data translation issues and requirements of the downstream applications like computational field simulation, rapid rototyping, computer graphics,computational manufacturing, and real-time rendering before they can be used. Automatic CAD model processing tools can significantly reduce the amount of time and cost associated with the manual processing.In this dissertaion, automated topology generation and feature removal techniques are developed to prepare suitable models with mimunum user interaction. A topology generation algorithm, commonly known as CAD repairing/healing, is presented to detect commonly found geometrical and topological issues like cracks, gaps, overlaps, intersections, T-connections, and no/invalid topology in the model, process them and build correct topological information. The present algorithm is based on the iterative vertex pair contraction and expansion operations called stitching and filling respectively. The algorithm closes small gaps/overlaps via the stitching operation and fills larger gaps by adding faces through the filling operation to process the model accurately. Processed models are guaranteed to be free of intersecting faces or surfaces. Moreover, the topology generation algorithm can process manifold as well as non-manifold models, which makes the procedure more general and flexible. This algorithm uses an automatic and adaptive distance threshold that enhances reliability of the process and preserves small features in the model. In addition, a spatial data structure, the octree, is used for searching and neighbor finding to process large models efficiently. In this way, the combination of generality, accuracy, reliability, and efficiency of this algorithm seems to be a significant improvement over existing techniques. Results are presented showing the effectiveness of the algorithm to process two- and three-dimensional configurations. Feature detection and removal and feature collapse algorithms are presented to detect and remove small features from CAD models automatically. The feature detection and removal algorithm uses a feature size measure based on the surface area and perimeter to detect small features accurately and remove them from the model. Small feature removal may create holes in the model that are post-processed using the stitching and/or filling operations of the topology generation algorithm. The feature collapse algorithm is based on the iterative vertex pair contraction operation, which is a generalization of an edge-collapse operation, to collapse small features. Unlike previous efforts that use edge-collapse as a dimension reduction operator, the feature collapse algorithm can pair up any arbitrary vertices and perform iterative vertex pair contraction to collapse small features as well as glue unconnected regions. Results showing the automatic detection and removal of most commonly found small features like small edges/faces, fillets, chamfers, nuts, and bolts from real mechanical parts are presented.