Research On Issues In Analvsis Feature Modeling

During the process of design and analysis, the analysis geometric model is usually generated from the design geometric model by simplification methods. However, due to the absence of an analysis geometric representation capable of supporting the seamless integration of CAD and CAE, and methods for the effective generation of the analysis geometric model, manual work and engineering experiences are still needed in the analysis geometric modeling process. This situation severely hinders the fast iteration of the design-analysis cycle. To solve these problems, a feature based analysis geometric representation is proposed in this paper, and their modeling methods are studied. Main contributions of this paper include:1. Feature based analysis geometric representation.The analysis feature model is proposed. Analysis features are defined to capture analysis semantics involved in the analysis modeling process. Low level associations between the design geometric model and the analysis geometric model are also included in the analysis feature model. With such information, the analysis feature model can enable the automated generation of the analysis model and bi-directional interaction between the design model and the analysis model.2. Generation of analysis feature models from boundary representation models.An approach to automated generation of analysis feature models from boundary representation models is proposed. Thin regions are identified by paring faces. Information about concave edges is utilized to improve the effectiveness of face paring, to reduce the number of times of volume decomposition, and to guide the extending and trimming of mid-surfaces.3. Generation of analysis feature models by feature conversion.An approach to automated generation of analysis feature models from design feature models is proposed. The problems of thin region recognition and idealized geometry extraction in3D are reduced to corresponding2D problems by taking advantage of swept volumes. The range of thin region recognition is enlarged by decomposing remnants of additive features into swept volumes. Missed and wrongly recognized thin regions are also processed, assuring correctness of the results.4. Construction of optimal symmetry cells for symmetry features.An approach is proposed to constructing optimal symmetry cells for rotationally symmetric models. A symmetry cell mesh is constructed using a modified Delaunay refinement mesh generation algorithm. The algorithm operates just on a local mesh. By introducing move of triangles and tetrahedrons, the symmetry boundaries of the local mesh are allowed to change, so as to maintain the consistency of the symmetry boundaries, and to guarantee the Delaunayness of the symmetry edges and faces. The symmetry cell mesh in2D case is proved to be optimal in the sense that its number of elements is within a constant factor of the smallest number.