In the mold flow analysis of plastic products, converting CAD models into solid meshes is a pre-requisite work in finite elements analysis. Mesh generation generally requires substantial manual efforts to edit meshes and is the most time-consuming, work. Recently, most mold flow analysis software has provided modules for automatic conversion of CAD models into meshes. As the geometric features are different, so are the suitable mesh elements for each of them. Feature recognition and feature simplification play an important role in automatic mesh generation because it enables the change of the mesh type in terms of the feature type, which can improve the accuracy and validity of the mold flow analysis. Typical features in CAD models are such as blend face, chamfer, hole, extrusion, rib and other particular features. Moreover, a feature may become even more complex when its boundary edges are blended or the face is sliced into several small faces. The aim of this project is to establish a technical road map for the development of feature recognition and feature simplification technologies under the Rhino CAD system. The proposed feature recognition algorithms are especially suitable for blend face, hole, extrusion and rib. Appropriate mesh elements are also indicated on each feature individually in order to improve the mesh quality and to reduce the total amount of meshes. For feature simplification, the primary task is to suppress various kinds of blend face, and convert them into original sharp edges or vertices, which can reduce bad meshes or tiny meshes that usually appear near the original blend faces. In this study, an integrated flowchart for feature recognition and feature simplification will be developed, and specific algorithms will be developed for each of the task features. Realistic CAD models will also be used to verify and validate the feasibility of the proposed algorithms. The results can be used to modify and improve the rules used in each of the algorithms. It is expected that the proposed feature recognition and feature simplification technologies can be employed to deal with more complex CAD models real industry.
|Effective start/end date||1/08/16 → 31/07/17|
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
- Feature recognition
- Fillet recognition
- Blend face recognition
- Protrusion recognition
- Feature simplification
- Solid mesh
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