It has been recognized that future intelligent design support environments need to reason about the geometry of products and to evaluate product functionality and performance against given constraints. A first step towards this goal is to provide a more robust information model which directly relates to design functionality or manufacturing characteristics, on which reasoning can be carried out. This has motivated research on feature-based modelling and reasoning. In this paper, an approach is presented to geometric reasoning based on graph grammar parsing. Our approach is presented to geometric reasoning based on graph grammar parsing. Our work combines methodologies from both design by features and feature recognition. A graph grammar is used to represent and manipulate features and geometric constraints. Geometric constraints are used within symbolical definitions of features constraints. Geometric constraints are used within symbolical definitions of features and also to define relative position and orientation of features. The graph grammar parsing is incorporated with knowledge-based inference to derive feature information and propagate constraints. This approach can be used for the transformation of feature information and to deal with feature interaction.
Automatic transformation of UML software specification into LQN performance models using graph grammar techniques
