Variational Direct Modeling: A Framework Towards Integration of Parametric Modeling and Direct Modeling in CAD. (April 2023)

• Record Type: Journal Article
• Authors: Zou, Qiang; Feng, Hsi-Yung; Gao, Shuming
• Is Part Of: Computer aided design. Volume 157(2023)
• Publication Date: 2023-04
• Subjects: Computer-aided design -- Solid modeling -- Parametric/direct integration -- Information inconsistency -- Validity maintenance -- Intelligent CAD; Computer-aided design -- Periodicals; Engineering design -- Data processing -- Periodicals; Computer graphics -- Periodicals; Conception technique -- Informatique -- Périodiques; Infographie -- Périodiques; Computer graphics; Engineering design -- Data processing; Periodicals; Electronic journals; 620.00420285
• DOI: 10.1016/j.cad.2022.103465
• Languages: English
• ISSNs: 0010-4485

Abstract

Abstract: Feature-based parametric modeling is the de facto standard in CAD. Boundary representation-based direct modeling is another CAD paradigm developed recently. They have complementary advantages and limitations, thereby offering huge potential for improvement towards an integrated CAD modeling scheme. Most existing integration methods are developed by industry and typically treat direct edits as pseudo-features, where little can be said about seamless integration. This paper presents an alternative method for seamless parametric/direct integration, which allows parametric and direct edits to work in a unified way. The fundamental issues and challenges of parametric/direct integration are first explained (i.e., parametric/direct edits will cause information inconsistencies among topological, geometric, and constraint information in the model, which consequently generates a non-solid and over-/under-constrained model, and resolving those information inconsistencies requires systematic decision-making among the many possible resolution options). A framework is then proposed to handle those information inconsistencies, based on a detection-then-resolution strategy. Algorithms that can systematically detect and resolve all possible types of information inconsistencies are also given to implement the framework. With them, model validity can be maintained during the whole model editing process, and then the discrepancy between direct edits and parametric edits can be resolved. The effectiveness of the proposed approach has been shown with a series of case studies and comparisons, based on a preliminary prototype. Graphical abstract: Highlights: Identifying the fundamental research problem and challenges of parametric/direct integration. Proposing a systematic framework for seamless parametric/direct integration. Formulating high-level parametric/direct integration tasks into well-defined math problems.