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    Theory and algorithms for swept manifold intersections

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    Recent developments in such fields as computer aided geometric design, geometric modeling, and computational topology have generated a spate of interest towards geometric objects called swept volumes. Besides their great applicability in various practical areas, the mere geometry and topology of these entities make them a perfect testbed for novel approaches aimed at analyzing and representing geometric objects. The structure of swept volumes reveals that it is also important to focus on a little simpler, although a very similar type of objects - swept manifolds. In particular, effective computability of swept manifold intersections is of major concern. The main goal of this dissertation is to conduct a study of swept manifolds and, based on the findings, develop methods for computing swept surface intersections. The twofold nature of this goal prompted a division of the work into two distinct parts. At first, a theoretical analysis of swept manifolds is performed, providing a better insight into the topological structure of swept manifolds and unveiling several important properties. In the course of the investigation, several subclasses of swept manifolds are introduced; in particular, attention is focused on regular and critical swept manifolds. Because of the high applicability, additional effort is put into analysis of two-dimensional swept manifolds - swept surfaces. Some of the valuable properties exhibited by such surfaces are generalized to higher dimensions by introducing yet another class of swept manifolds - recursive swept manifolds. In the second part of this work, algorithms for finding swept surface intersections are developed. The need for such algorithms is necessitated by a specific structure of swept surfaces that precludes direct employment of existing intersection methods. The new algorithms are designed by utilizing the underlying ideas of existing intersection techniques and making necessary technical modifications. Such modifications are achieved by employing properties of swept surfaces obtained in the course of the theoretical study. The intersection problems is also considered from a little different prospective. A novel, homology based approach to local characterization of intersections of submanifolds and s-subvarieties of a Euclidean space is presented. It provides a method for distinguishing between transverse and tangential intersection points and determining, in some cases, whether the intersection point belongs to a boundary. At the end, several possible applications of the obtained results are described, including virtual sculpting and modeling of heterogeneous materials

    BVH์™€ ํ† ๋Ÿฌ์Šค ํŒจ์น˜๋ฅผ ์ด์šฉํ•œ ๊ณก๋ฉด ๊ต์ฐจ๊ณก์„  ์—ฐ์‚ฐ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2021.8. ๊น€๋ช…์ˆ˜.๋‘ ๋ณ€์ˆ˜๋ฅผ ๊ฐ€์ง€๋Š” B-์Šคํ”Œ๋ผ์ธ ์ž์œ ๊ณก๋ฉด์˜ ๊ณก๋ฉด๊ฐ„ ๊ต์ฐจ๊ณก์„ ๊ณผ ์ž๊ฐ€ ๊ต์ฐจ๊ณก์„ , ๊ทธ๋ฆฌ๊ณ  ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ๊ณก์„ ์„ ๊ตฌํ•˜๋Š” ํšจ์œจ์ ์ด๊ณ  ์•ˆ์ •์ ์ธ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ฐœ๋ฐœํ•˜๋Š” ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•์€ ์ตœํ•˜๋‹จ ๋…ธ๋“œ์— ์ตœ๋Œ€ ์ ‘์ด‰ ํ† ๋Ÿฌ์Šค๋ฅผ ๊ฐ€์ง€๋Š” ๋ณตํ•ฉ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ ๊ตฌ์กฐ์— ๊ธฐ๋ฐ˜์„ ๋‘๊ณ  ์žˆ๋‹ค. ์ด ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ ๊ตฌ์กฐ๋Š” ๊ณก๋ฉด๊ฐ„ ๊ต์ฐจ๋‚˜ ์ž๊ฐ€ ๊ต์ฐจ๊ฐ€ ๋ฐœ์ƒํ•  ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ๋Š” ์ž‘์€ ๊ณก๋ฉด ์กฐ๊ฐ ์Œ๋“ค์˜ ๊ธฐํ•˜ํ•™์  ๊ฒ€์ƒ‰์„ ๊ฐ€์†ํ™”ํ•œ๋‹ค. ์ตœ๋Œ€ ์ ‘์ด‰ ํ† ๋Ÿฌ์Šค๋Š” ์ž๊ธฐ๊ฐ€ ๊ทผ์‚ฌํ•œ C2-์—ฐ์† ์ž์œ ๊ณก๋ฉด๊ณผ 2์ฐจ ์ ‘์ด‰์„ ๊ฐ€์ง€๋ฏ€๋กœ ์ฃผ์–ด์ง„ ๊ณก๋ฉด์—์„œ ๋‹ค์–‘ํ•œ ๊ธฐํ•˜ ์—ฐ์‚ฐ์˜ ์ •๋ฐ€๋„๋ฅผ ํ–ฅ์ƒ์‹œํ‚ค๋Š”๋ฐ ํ•„์ˆ˜์ ์ธ ์—ญํ• ์„ ํ•œ๋‹ค. ํšจ์œจ์ ์ธ ๊ณก๋ฉด๊ฐ„ ๊ต์ฐจ๊ณก์„  ๊ณ„์‚ฐ์„ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•ด, ๋ฏธ๋ฆฌ ๋งŒ๋“ค์–ด์ง„, ์ตœํ•˜๋‹จ ๋…ธ๋“œ์— ์ตœ๋Œ€ ์ ‘์ด‰ ํ† ๋Ÿฌ์Šค๊ฐ€ ์žˆ์œผ๋ฉฐ ๊ตฌํ˜•๊ตฌ๋ฉด ํŠธ๋ฆฌ๋ฅผ ๊ฐ€์ง€๋Š” ๋ณตํ•ฉ ์ดํ•ญ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ ๊ตฌ์กฐ๋ฅผ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์ตœ๋Œ€ ์ ‘์ด‰ ํ† ๋Ÿฌ์Šค๋Š” ๊ฑฐ์˜ ๋ชจ๋“  ๊ณณ์—์„œ ์ ‘์„ ๊ต์ฐจ๊ฐ€ ๋ฐœ์ƒํ•˜๋Š”, ์ž๋ช…ํ•˜์ง€ ์•Š์€ ๊ณก๋ฉด๊ฐ„ ๊ต์ฐจ๊ณก์„  ๊ณ„์‚ฐ ๋ฌธ์ œ์—์„œ๋„ ํšจ์œจ์ ์ด๊ณ  ์•ˆ์ •์ ์ธ ๊ฒฐ๊ณผ๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์„ ๊ตฌํ•˜๋Š” ๋ฌธ์ œ๋Š” ์ฃผ๋กœ ๋งˆ์ดํ„ฐ ์  ๋•Œ๋ฌธ์— ๊ณก๋ฉด๊ฐ„ ๊ต์ฐจ๊ณก์„ ์„ ๊ณ„์‚ฐํ•˜๋Š” ๊ฒƒ ๋ณด๋‹ค ํ›จ์”ฌ ๋” ์–ด๋ ต๋‹ค. ์ž๊ฐ€ ๊ต์ฐจ ๊ณก๋ฉด์€ ๋งˆ์ดํ„ฐ ์  ๋ถ€๊ทผ์—์„œ ๋ฒ•์„  ๋ฐฉํ–ฅ์ด ๊ธ‰๊ฒฉํžˆ ๋ณ€ํ•˜๋ฉฐ, ๋งˆ์ดํ„ฐ ์ ์€ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์˜ ๋์ ์— ์œ„์น˜ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๋งˆ์ดํ„ฐ ์ ์€ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก๋ฉด์˜ ๊ธฐํ•˜ ์—ฐ์‚ฐ ์•ˆ์ •์„ฑ์— ํฐ ๋ฌธ์ œ๋ฅผ ์ผ์œผํ‚จ๋‹ค. ๋งˆ์ดํ„ฐ ์ ์„ ์•ˆ์ •์ ์œผ๋กœ ๊ฐ์ง€ํ•˜์—ฌ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์˜ ๊ณ„์‚ฐ์„ ์šฉ์ดํ•˜๊ฒŒ ํ•˜๊ธฐ ์œ„ํ•ด, ์ž์œ ๊ณก๋ฉด์„ ์œ„ํ•œ ๋ณตํ•ฉ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ ๊ตฌ์กฐ์— ์ ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ์‚ผํ•ญ ํŠธ๋ฆฌ ๊ตฌ์กฐ๋ฅผ ์ œ์‹œํ•œ๋‹ค. ํŠนํžˆ, ๋‘ ๋ณ€์ˆ˜๋ฅผ ๊ฐ€์ง€๋Š” ๊ณก๋ฉด์˜ ๋งค๊ฐœ๋ณ€์ˆ˜์˜์—ญ์—์„œ ๋งˆ์ดํ„ฐ ์ ์„ ์ถฉ๋ถ„ํžˆ ์ž‘์€ ์‚ฌ๊ฐํ˜•์œผ๋กœ ๊ฐ์‹ธ๋Š” ํŠน๋ณ„ํ•œ ํ‘œํ˜„ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ ‘์„ ๊ต์ฐจ์™€ ๋งˆ์ดํ„ฐ ์ ์„ ๊ฐ€์ง€๋Š”, ์•„์ฃผ ์ž๋ช…ํ•˜์ง€ ์•Š์€ ์ž์œ ๊ณก๋ฉด ์˜ˆ์ œ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ƒˆ ๋ฐฉ๋ฒ•์ด ํšจ๊ณผ์ ์ž„์„ ์ž…์ฆํ•œ๋‹ค. ๋ชจ๋“  ์‹คํ—˜ ์˜ˆ์ œ์—์„œ, ๊ธฐํ•˜์š”์†Œ๋“ค์˜ ์ •ํ™•๋„๋Š” ํ•˜์šฐ์Šค๋„๋ฅดํ”„ ๊ฑฐ๋ฆฌ์˜ ์ƒํ•œ๋ณด๋‹ค ๋‚ฎ์Œ์„ ์ธก์ •ํ•˜์˜€๋‹ค.We present a new approach to the development of efficient and stable algorithms for intersecting freeform surfaces, including the surface-surface-intersection and the surface self-intersection of bivariate rational B-spline surfaces. Our new approach is based on a hybrid Bounding Volume Hierarchy(BVH) that stores osculating toroidal patches in the leaf nodes. The BVH structure accelerates the geometric search for the potential pairs of local surface patches that may intersect or self-intersect. Osculating toroidal patches have second-order contact with C2-continuous freeform surfaces that they approximate, which plays an essential role in improving the precision of various geometric operations on the given surfaces. To support efficient computation of the surface-surface-intersection curve, we design a hybrid binary BVH that is basically a pre-built Rectangle-Swept Sphere(RSS) tree enhanced with osculating toroidal patches in their leaf nodes. Osculating toroidal patches provide efficient and robust solutions to the problem even in the non-trivial cases of handling two freeform surfaces intersecting almost tangentially everywhere. The surface self-intersection problem is considerably more difficult than computing the intersection of two different surfaces, mainly due to the existence of miter points. A self-intersecting surface changes its normal direction dramatically around miter points, located at the open endpoints of the self-intersection curve. This undesirable behavior causes serious problems in the stability of geometric algorithms on self-intersecting surfaces. To facilitate surface self-intersection computation with a stable detection of miter points, we propose a ternary tree structure for the hybrid BVH of freeform surfaces. In particular, we propose a special representation of miter points using sufficiently small quadrangles in the parameter domain of bivariate surfaces and expand ideas to offset surfaces. We demonstrate the effectiveness of the proposed new approach using some highly non-trivial examples of freeform surfaces with tangential intersections and miter points. In all the test examples, the closeness of geometric entities is measured under the Hausdorff distance upper bound.Chapter 1 Introduction 1 1.1 Background 1 1.2 Surface-Surface-Intersection 5 1.3 Surface Self-Intersection 8 1.4 Main Contribution 12 1.5 Thesis Organization 14 Chapter 2 Preliminaries 15 2.1 Differential geometry of surfaces 15 2.2 Bezier curves and surfaces 17 2.3 Surface approximation 19 2.4 Torus 21 2.5 Summary 24 Chapter 3 Previous Work 25 3.1 Surface-Surface-Intersection 25 3.2 Surface Self-Intersection 29 3.3 Summary 32 Chapter 4 Bounding Volume Hierarchy for Surface Intersections 33 4.1 Binary Structure 33 4.1.1 Hierarchy of Bilinear Surfaces 34 4.1.2 Hierarchy of Planar Quadrangles 37 4.1.3 Construction of Leaf Nodes with Osculating Toroidal Patches 41 4.2 Ternary Structure 44 4.2.1 Miter Points 47 4.2.2 Leaf Nodes 50 4.2.3 Internal Nodes 51 4.3 Summary 56 Chapter 5 Surface-Surface-Intersection 57 5.1 BVH Traversal 58 5.2 Construction of SSI Curve Segments 59 5.2.1 Merging SSI Curve Segments with G1-Biarcs 60 5.2.2 Measuring the SSI Approximation Error Using G1-Biarcs 63 5.3 Tangential Intersection 64 5.4 Summary 65 Chapter 6 Surface Self-Intersection 67 6.1 Preprocessing 68 6.2 BVH Traversal 69 6.3 Construction of Intersection Curve Segments 70 6.4 Summary 72 Chapter 7 Trimming Offset Surfaces with Self-Intersection Curves 74 7.1 Offset Surface and Ternary Hybrid BVH 75 7.2 Preprocessing 77 7.3 Merging Intersection Curve Segments 81 7.4 Summary 84 Chapter 8 Experimental Results 85 8.1 Surface-Surface-Intersection 85 8.2 Surface Self-Intersection 97 8.2.1 Regular Surfaces 97 8.2.2 Offset Surfaces 100 Chapter 9 Conclusion 106 Bibliography 108 ์ดˆ๋ก 120๋ฐ•

    ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ฒ€์ถœ ๋ฐ ์ œ๊ฑฐ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2020. 2. ๊น€๋ช…์ˆ˜.Offset curves and surfaces have many applications in computer-aided design and manufacturing, but the self-intersections and redundancies must be trimmed away for their practical use. We present a new method for offset curve and surface trimming that detects the self-intersections and eliminates the redundant parts of an offset curve and surface that are closer than the offset distance to the original curve and surface. We first propose an offset trimming method based on constructing geometric constraint equations. We formulate the constraint equations of the self-intersections of an offset curve and surface in the parameter domain of the original curve and surface. Numerical computations based on the regularity and intrinsic properties of the given input curve and surface is carried out to compute the solution of the constraint equations. The method deals with numerical instability around near-singular regions of an offset surface by using osculating tori that can be constructed in a highly stable way, i.e., by offsetting the osculating torii of the given input regular surface. We reveal the branching structure and the terminal points from the complete self-intersection curves of the offset surface. From the observation that the trimming method based on the multivariate equation solving is computationally expensive, we also propose an acceleration technique to trim an offset curve and surface. The alternative method constructs a bounding volume hierarchy specially designed to enclose the offset curve and surface and detects the self-collision of the bounding volumes instead. In the case of an offset surface, the thickness of the bounding volumes is indirectly determined based on the maximum deviations of the positions and the normals between the given input surface patches and their osculating tori. For further acceleration, the bounding volumes are pruned as much as possible during self-collision detection using various geometric constraints imposed on the offset surface. We demonstrate the effectiveness of the new trimming method using several non-trivial test examples of offset trimming. Lastly, we investigate the problem of computing the Voronoi diagram of a freeform surface using the offset trimming technique for surfaces. By trimming the offset surface with a gradually changing offset radius, we compute the boundary of the Voronoi cells that appear in the concave side of the given input surface. In particular, we interpret the singular and branching points of the self-intersection curves of the trimmed offset surfaces in terms of the boundary elements of the Voronoi diagram.์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์€ computer-aided design (CAD)์™€ computer-aided manufacturing (CAM)์—์„œ ๋„๋ฆฌ ์ด์šฉ๋˜๋Š” ์—ฐ์‚ฐ๋“ค ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ํ•˜์ง€๋งŒ ์‹ค์šฉ์ ์ธ ํ™œ์šฉ์„ ์œ„ํ•ด์„œ๋Š” ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์—์„œ ์ƒ๊ธฐ๋Š” ์ž๊ฐ€ ๊ต์ฐจ๋ฅผ ์ฐพ๊ณ  ์ด๋ฅผ ๊ธฐ์ค€์œผ๋กœ ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์—์„œ ์›๋ž˜์˜ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์— ๊ฐ€๊นŒ์šด ๋ถˆํ•„์š”ํ•œ ์˜์—ญ์„ ์ œ๊ฑฐํ•˜์—ฌ์•ผํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์—์„œ ์ƒ๊ธฐ๋Š” ์ž๊ฐ€ ๊ต์ฐจ๋ฅผ ๊ณ„์‚ฐํ•˜๊ณ , ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์—์„œ ์ƒ๊ธฐ๋Š” ๋ถˆํ•„์š”ํ•œ ์˜์—ญ์„ ์ œ๊ฑฐํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์šฐ์„  ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ์ ๋“ค๊ณผ ๊ทธ ๊ต์ฐจ์ ๋“ค์ด ๊ธฐ์ธํ•œ ์›๋ž˜ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ ๋“ค์ด ์ด๋ฃจ๋Š” ํ‰๋ฉด ์ด๋“ฑ๋ณ€ ์‚ผ๊ฐํ˜• ๊ด€๊ณ„๋กœ๋ถ€ํ„ฐ ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ์ ์˜ ์ œ์•ฝ ์กฐ๊ฑด์„ ๋งŒ์กฑ์‹œํ‚ค๋Š” ๋ฐฉ์ •์‹๋“ค์„ ์„ธ์šด๋‹ค. ์ด ์ œ์•ฝ์‹๋“ค์€ ์›๋ž˜ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ๋ณ€์ˆ˜ ๊ณต๊ฐ„์—์„œ ํ‘œํ˜„๋˜๋ฉฐ, ์ด ๋ฐฉ์ •์‹๋“ค์˜ ํ•ด๋Š” ๋‹ค๋ณ€์ˆ˜ ๋ฐฉ์ •์‹์˜ ํ•ด๋ฅผ ๊ตฌํ•˜๋Š” solver๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ตฌํ•œ๋‹ค. ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ๊ฒฝ์šฐ, ์›๋ž˜ ๊ณก๋ฉด์˜ ์ฃผ๊ณก๋ฅ  ์ค‘ ํ•˜๋‚˜๊ฐ€ ์˜คํ”„์…‹ ๋ฐ˜์ง€๋ฆ„์˜ ์—ญ์ˆ˜์™€ ๊ฐ™์„ ๋•Œ ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ๋ฒ•์„ ์ด ์ •์˜๊ฐ€ ๋˜์ง€ ์•Š๋Š” ํŠน์ด์ ์ด ์ƒ๊ธฐ๋Š”๋ฐ, ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์ด ์ด ๋ถ€๊ทผ์„ ์ง€๋‚  ๋•Œ๋Š” ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์˜ ๊ณ„์‚ฐ์ด ๋ถˆ์•ˆ์ •ํ•ด์ง„๋‹ค. ๋”ฐ๋ผ์„œ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์ด ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ํŠน์ด์  ๋ถ€๊ทผ์„ ์ง€๋‚  ๋•Œ๋Š” ์˜คํ”„์…‹ ๊ณก๋ฉด์„ ์ ‘์ด‰ ํ† ๋Ÿฌ์Šค๋กœ ์น˜ํ™˜ํ•˜์—ฌ ๋” ์•ˆ์ •๋œ ๋ฐฉ๋ฒ•์œผ๋กœ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์„ ๊ตฌํ•œ๋‹ค. ๊ณ„์‚ฐ๋œ ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์œผ๋กœ๋ถ€ํ„ฐ ๊ต์ฐจ ๊ณก์„ ์˜ xyzxyz-๊ณต๊ฐ„์—์„œ์˜ ๋ง๋‹จ ์ , ๊ฐ€์ง€ ๊ตฌ์กฐ ๋“ฑ์„ ๋ฐํžŒ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ๋˜ํ•œ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ ๊ธฐ๋ฐ˜์˜ ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„  ๊ฒ€์ถœ์„ ๊ฐ€์†ํ™”ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ์€ ๊ธฐ์ € ๊ณก์„  ๋ฐ ๊ณก๋ฉด์„ ๋‹จ์ˆœํ•œ ๊ธฐํ•˜๋กœ ๊ฐ์‹ธ๊ณ  ๊ธฐํ•˜ ์—ฐ์‚ฐ์„ ์ˆ˜ํ–‰ํ•จ์œผ๋กœ์จ ๊ฐ€์†ํ™”์— ๊ธฐ์—ฌํ•œ๋‹ค. ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์„ ๊ตฌํ•˜๊ธฐ ์œ„ํ•˜์—ฌ, ๋ณธ ๋…ผ๋ฌธ์€ ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ ๊ตฌ์กฐ๋ฅผ ๊ธฐ์ € ๊ณก๋ฉด์˜ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ๊ณผ ๊ธฐ์ € ๊ณก๋ฉด์˜ ๋ฒ•์„  ๊ณก๋ฉด์˜ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ์˜ ๊ตฌ์กฐ๋กœ๋ถ€ํ„ฐ ๊ณ„์‚ฐํ•˜๋ฉฐ ์ด๋•Œ ๊ฐ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ์˜ ๋‘๊ป˜๋ฅผ ๊ณ„์‚ฐํ•œ๋‹ค. ๋˜ํ•œ, ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ ์ค‘์—์„œ ์‹ค์ œ ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ์— ๊ธฐ์—ฌํ•˜์ง€ ์•Š๋Š” ๋ถ€๋ถ„์„ ๊นŠ์€ ์žฌ๊ท€ ์ „์— ์ฐพ์•„์„œ ์ œ๊ฑฐํ•˜๋Š” ์—ฌ๋Ÿฌ ์กฐ๊ฑด๋“ค์„ ๋‚˜์—ดํ•œ๋‹ค. ํ•œํŽธ, ์ž๊ฐ€ ๊ต์ฐจ๊ฐ€ ์ œ๊ฑฐ๋œ ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์€ ๊ธฐ์ € ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ๋ณด๋กœ๋…ธ์ด ๊ตฌ์กฐ์™€ ๊นŠ์€ ๊ด€๋ จ์ด ์žˆ๋Š” ๊ฒƒ์ด ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ž์œ  ๊ณก๋ฉด์˜ ์—ฐ์†๋œ ์˜คํ”„์…‹ ๊ณก๋ฉด๋“ค๋กœ๋ถ€ํ„ฐ ์ž์œ  ๊ณก๋ฉด์˜ ๋ณด๋กœ๋…ธ์ด ๊ตฌ์กฐ๋ฅผ ์œ ์ถ”ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ํŠนํžˆ, ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„  ์ƒ์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ๊ฐ€์ง€ ์ ์ด๋‚˜ ๋ง๋‹จ ์ ๊ณผ ๊ฐ™์€ ํŠน์ด์ ๋“ค์ด ์ž์œ  ๊ณก๋ฉด์˜ ๋ณด๋กœ๋…ธ์ด ๊ตฌ์กฐ์—์„œ ์–ด๋–ป๊ฒŒ ํ•ด์„๋˜๋Š”์ง€ ์ œ์‹œํ•œ๋‹ค.1. Introduction 1 1.1 Background and Motivation 1 1.2 Research Objectives and Approach 7 1.3 Contributions and Thesis Organization 11 2. Preliminaries 14 2.1 Curve and Surface Representation 14 2.1.1 Bezier Representation 14 2.1.2 B-spline Representation 17 2.2 Differential Geometry of Curves and Surfaces 19 2.2.1 Differential Geometry of Curves 19 2.2.2 Differential Geometry of Surfaces 21 3. Previous Work 23 3.1 Offset Curves 24 3.2 Offset Surfaces 27 3.3 Offset Curves on Surfaces 29 4. Trimming Offset Curve Self-intersections 32 4.1 Experimental Results 35 5. Trimming Offset Surface Self-intersections 38 5.1 Constraint Equations for Offset Self-Intersections 38 5.1.1 Coplanarity Constraint 39 5.1.2 Equi-angle Constraint 40 5.2 Removing Trivial Solutions 40 5.3 Removing Normal Flips 41 5.4 Multivariate Solver for Constraints 43 5.A Derivation of f(u,v) 46 5.B Relationship between f(u,v) and Curvatures 47 5.3 Trimming Offset Surfaces 50 5.4 Experimental Results 53 5.5 Summary 57 6. Acceleration of trimming offset curves and surfaces 62 6.1 Motivation 62 6.2 Basic Approach 67 6.3 Trimming an Offset Curve using the BVH 70 6.4 Trimming an Offset Surface using the BVH 75 6.4.1 Offset Surface BVH 75 6.4.2 Finding Self-intersections in Offset Surface Using BVH 87 6.4.3 Tracing Self-intersection Curves 98 6.5 Experimental Results 100 6.6 Summary 106 7. Application of Trimming Offset Surfaces: 3D Voronoi Diagram 107 7.1 Background 107 7.2 Approach 110 7.3 Experimental Results 112 7.4 Summary 114 8. Conclusion 119 Bibliography iDocto

    Volumetric Untrimming: Precise decomposition of trimmed trivariates into tensor products

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    3D objects, modeled using Computer Aided Geometric Design tools, are traditionally represented using a boundary representation (B-rep), and typically use spline functions to parameterize these boundary surfaces. However, recent development in physical analysis, in isogeometric analysis (IGA) in specific, necessitates a volumetric parametrization of the interior of the object. IGA is performed directly by integrating over the spline spaces of the volumetric spline representation of the object. Typically, tensor-product B-spline trivariates are used to parameterize the volumetric domain. A general 3D object, that can be modeled in contemporary B-rep CAD tools, is typically represented using trimmed B-spline surfaces. In order to capture the generality of the contemporary B-rep modeling space, while supporting IGA needs, Massarwi and Elber (2016) proposed the use of trimmed trivariates volumetric elements. However, the use of trimmed geometry makes the integration process more difficult since integration over trimmed B-spline basis functions is a highly challenging task. In this work, we propose an algorithm that precisely decomposes a trimmed B-spline trivariate into a set of (singular only on the boundary) tensor-product B-spline trivariates, that can be utilized to simplify the integration process in IGA. The trimmed B-spline trivariate is first subdivided into a set of trimmed B\'ezier trivariates, at all its internal knots. Then, each trimmed B\'ezier trivariate, is decomposed into a set of mutually exclusive tensor-product B-spline trivariates, that precisely cover the entire trimmed domain. This process, denoted untrimming, can be performed in either the Euclidean space or the parametric space of the trivariate. We present examples on complex trimmed trivariates' based geometry, and we demonstrate the effectiveness of the method by applying IGA over the (untrimmed) results.Comment: 18 pages, 32 figures. Contribution accepted in International Conference on Geometric Modeling and Processing (GMP 2019

    Collision Detection and Merging of Deformable B-Spline Surfaces in Virtual Reality Environment

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    This thesis presents a computational framework for representing, manipulating and merging rigid and deformable freeform objects in virtual reality (VR) environment. The core algorithms for collision detection, merging, and physics-based modeling used within this framework assume that all 3D deformable objects are B-spline surfaces. The interactive design tool can be represented as a B-spline surface, an implicit surface or a point, to allow the user a variety of rigid or deformable tools. The collision detection system utilizes the fact that the blending matrices used to discretize the B-spline surface are independent of the position of the control points and, therefore, can be pre-calculated. Complex B-spline surfaces can be generated by merging various B-spline surface patches using the B-spline surface patches merging algorithm presented in this thesis. Finally, the physics-based modeling system uses the mass-spring representation to determine the deformation and the reaction force values provided to the user. This helps to simulate realistic material behaviour of the model and assist the user in validating the design before performing extensive product detailing or finite element analysis using commercially available CAD software. The novelty of the proposed method stems from the pre-calculated blending matrices used to generate the points for graphical rendering, collision detection, merging of B-spline patches, and nodes for the mass spring system. This approach reduces computational time by avoiding the need to solve complex equations for blending functions of B-splines and perform the inversion of large matrices. This alternative approach to the mechanical concept design will also help to do away with the need to build prototypes for conceptualization and preliminary validation of the idea thereby reducing the time and cost of concept design phase and the wastage of resources

    Self-Intersection Computation for Freeform Surfaces Based on a Regional Representation Scheme for Miter Points

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    We present an efficient and robust algorithm for computing the self-intersection of a freeform surface, based on a special representation of miter points, using sufficiently small quadrangles in the parameter domain. A self-intersecting surface changes its normal direction quite dramatically around miter points, located at the open endpoints of the self-intersection curve. This undesirable behavior causes serious problems in the stability of geometric algorithms on the surface. To facilitate a stable detection of miter points, we employ osculating toroidal patches and their intersections, and consider a gradual change to degenerate intersections as a signal for the detection of miter points. The exact location of each miter point is bounded by a tiny ball in the Euclidean space and is also represented as a small quadrangle in the parameter space. The surface self-intersection curve is then constructed, using a hybrid Bounding Volume Hierarchy (BVH), where the leaf nodes contain osculating toroidal patches and miter quadrangles. We demonstrate the effectiveness of our approach by using test examples of computing the self-intersection of freeform surfaces

    Computational Intelligence In CAD/CAM Applications

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    This paper presents a fundamental, direct, and powerful approach to the surface/surface intersection problem in CAD/CAM applications. The algorithm is designed and implemented in three steps: a) Preprocessing- locate the potentially intersecting sections of the surfaces and decompose the surfaces into surface elements within specified flatness tolerance; b) Intersection- decompose the possibly intersecting pairs of surface elements into continuous surface triangulations to find the approximate intersections between the pairs of surface elements; c) Postprocessing-assemble the intersection primitives into curves of intersection, refine the accuracy of computed intersection points, and compact the intersection curves. This surface/surface intersection algorithm is applicable to the widest class, Cยฐ, of parametric surfaces, an enhancement over the existing algorithms applicable to only Ck, kโ‰ฅ 1, surfaces. This implementation, based on computational intelligence, requires no human interaction for intersection curve pattern recognition
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