Automatic shape adaptation for parametric solid models

Abstract

Adaptation, as is well known, plays a fundamental role in Case-Based Design. However, after decades of efforts, automatic adaptation approach is still rare. In common design works, the first thing one will usually do is choosing a start-up model (a candidate model) of moderate complexity based on a simple query model possessing primary design constraints. To enable the candidate model to smartly adapt its shape to that of the query model according to the embedded constraints, a novel automatic shape adaptation approach is proposed in this paper. First, to determine the corresponding faces between two non-preregistered models as relevant elements, a shape frame concept and its quantitative descriptor are defined. Second, to unify the representation of seemingly different but inherently consistent dimensions, a promotion method is adopted. Third, based on the corresponding faces and the promoted dimension representation, the corresponding dimensions between the two parametric solid models are identified. Finally, the parametric information is smoothly transferred from the query model to the candidate model as design constraints, and the shape of the candidate model is automatically adapted to the query model. Besides that, a prototype system is also implemented to verify the effectiveness of the automatic shape adaptation approach.