Estimating the impact of large design changes on field problems

• Authors: Sankara Hari Gopalakrishnan;Krishnan Suresh
• Venue: Proceedings of the 2007 ACM symposium on Solid and physical modeling
• Year: 2007

CAD systems today are feature-based in that they represent geometry via a collection of features, and associated feature parameters. During the design process, feature parameters are optimized to meet various design objectives including functionality, manufacturability, aesthetics, etc. This paper focuses on predicting the impact of parametric feature changes on quantities of interest, such as average stress within a given region, etc. When the parametric change is sufficiently small, one can rely on classic shape sensitivity and reanalysis methods to rapidly predict the desired quantity of interest. However, when the parametric changes are large, both methods are unreliable. In this paper, we propose an alternate methodology for predicting the impact of large parametric feature changes on field problems, and thereby opening fundamentally new avenues for design exploration and parametric optimization. The proposed methodology is based on the novel concept of feature sensitivity, a generalization of topological sensitivity. Topological sensitivity captures the first-order change in quantities of interest when a small spherical hole is created within an existing geometry. This is generalized here to an arbitrary collection of internal or boundary features. Subsequently, we demonstrate its application to large parametric feature changes. The methodology is illustrated via numerical experiments involving a 2-D scalar field problem.