Classification of Edges and its Application in Determining Visibility

A new hidden-line algorithm is proposed for illustrating objects consisting of plane faces. The algorithm determines the degree of edge and classifies edges and faces into contoural and non-contoural. To reduce memory requirements, sequential files and sorting are used. The algorithm is particularly intended for illustrating complex objects, such as curved surfaces approximated by plane face

Hidden Curve Elimination of Trimmed Surfaces Using Bézier Clipping

Shaded display is popular for displaying curved surfaces because of the realistic appearance of the images produced. In the field of computer aided geometric design, however, line drawings are more commonly used. For accurate evaluation of the curved surfaces in these designs, the conventional method of approximating curved surfaces with polygons is insufficient. In this paper we will present a method of hidden line elimination without resorting to polygonal approximation. The method provides the designer smoother, more precise isoparametric curves than traditional polygonal approximation methods. In addition, the method can draw precise silhouette curves, trimming curves, drawings of patterns represented by curves on the surface, and contour lines. Furthermore, the method is valid even for surfaces which penetrate each other

Determining the parametric effectiveness of a CAD model

The motivation for this paper is to present an approach for rating the quality of the parameters in a computer-aided design model for use as optimization variables. Parametric Effectiveness is computed as the ratio of change in performance achieved by perturbing the parameters in the optimum way, to the change in performance that would be achieved by allowing the boundary of the model to move without the constraint on shape change enforced by the CAD parameterization. The approach is applied in this paper to optimization based on adjoint shape sensitivity analyses. The derivation of parametric effectiveness is presented for optimization both with and without the constraint of constant volume. In both cases, the movement of the boundary is normalized with respect to a small root mean squared movement of the boundary. The approach can be used to select an initial search direction in parameter space, or to select sets of model parameters which have the greatest ability to improve model performance. The approach is applied to a number of example 2D and 3D FEA and CFD problems