• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.784-787
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• 2002

The NURBS surfaces are widely employed for exchanging geometric models between different CAD/CAE systems. However if the input NURBS surfaces are poorly parameterized, most surface meshing algorithms may fail or the constructed meshes can be ill-conditioned. In this paper presents a new method is presented that can generate well conditioned meshes even on poorly parameterized NURBS surfaces by regenerating NURBS surfaces. To begin with, adequate Points are sample on original poorly parameterized surfaces and new surfaces are created by interpolating these points. And then. mesh generation is performed on new surfaces. With this method, models with poorly parameterized NURBS surfaces can be meshed successfully.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1302-1311
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• 2003

This paper presents a more stable method of multiresolution editing for a triangular mesh. The basic idea of our paper is to embed an editing area of a mesh onto a 2D region and to produce 3D surfaces which interpolate the editing-information. In this paper, we adopt the extended convex combination approach based on the shape-preserving parameterization for the embedding, which guarantees no self-intersection on the 2D embedded mesh. That is, the result of the embedding is stable. Moreover, we adopt the multi-level B-spline approach to generate the surface containing all of 3D editing-information, which can make us control the editing area in several levels. Hence, this method supports interactive editing and thus can produce intuitive editing results.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.6
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• pp.189-196
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• 2003

The NURBS surfaces are widely employed for exchanging geometric models between different CAD/CAE systems. However if the input NURBS surfaces are poorly parameterized, most surface meshing algorithms may fail or the constructed meshes can be ill-conditioned. In this paper presents a new method is presented that can generate well conditioned meshes even on poorly parameterized NURBS surfaces by regenerating NURBS surfaces. To begin with, adequate points are sampled on original poorly parameterized surfaces and new surfaces are created by interpolating these points. And then, mesh generation is performed on new surfaces. With this method, models with poorly parameterized NURBS surfaces can be meshed successfully.

• Korean Journal of Computational Design and Engineering
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• v.13 no.6
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• pp.450-458
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• 2008

Recently, Cartesian grid approach has been popular to generate grid meshes for complex geometries in CFD (Computational Fluid Dynamics) because it is based on the non-body-fitted technique. This paper presents a method of an octree generation and boundary cell clipping using section curves for fast octree generation and elimination of redundant intersections between boundary cells and triangles from 3D triangular mesh. The proposed octree generation method uses 2D Scan-Converting line algorithm, and the clipping is done by parameterization of vertices from section curves. Experimental results provide octree generation time as well as Cut-cell clipping time of several models. The result shows that the proposed octree generation is fast and has linear relationship between grid generation time and the number of cut-cells.

• Journal of the Korea Computer Graphics Society
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• v.7 no.3
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• pp.9-18
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• 2001

Feature detection is important in various mesh processing techniques, such as mesh editing, mesh morphing, mesh compression, and mesh signal processing. In this paper, we propose a geometric snake as an interactive tool for feature detection on a 3D triangular mesh. A geometric snake is an extension of an image snake, which is an active contour model that slithers from its initial position specified by the user to a nearby feature while minimizing an energy functional. To constrain the movement of a geometric snake onto the surface of a mesh, we use the parameterization of the surrounding region of a geometric snake. Although the definition of a feature may vary among applications, we use the normal changes of faces to detect features on a mesh.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.216-221
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• 2008

Shape design optimization for linear elasticity problem is performed using isogeometric analysis method. In many design optimization problems for real engineering models, initial raw data usually comes from CAD modeler. Then designer should convert this CAD data into finite element mesh data because conventional design optimization tools are generally based on finite element analysis. During this conversion there is some numerical error due to a geometry approximation, which causes accuracy problems in not only response analysis but also design sensitivity analysis. As a remedy of this phenomenon, the isogeometric analysis method is one of the promising approaches of shape design optimization. The main idea of isogeometric analysis is that the basis functions used in analysis is exactly same as ones which represent the geometry, and this geometrically exact model can be used shape sensitivity analysis and design optimization as well. In shape design sensitivity point of view, precise shape sensitivity is very essential for gradient-based optimization. In conventional finite element based optimization, higher order information such as normal vector and curvature term is inaccurate or even missing due to the use of linear interpolation functions. On the other hands, B-spline basis functions have sufficient continuity and their derivatives are smooth enough. Therefore normal vector and curvature terms can be exactly evaluated, which eventually yields precise optimal shapes. In this article, isogeometric analysis method is utilized for the shape design optimization. By virtue of B-spline basis function, an exact geometry can be handled without finite element meshes. Moreover, initial CAD data are used throughout the optimization process, including response analysis, shape sensitivity analysis, design parameterization and shape optimization, without subsequent communication with CAD description.