17 research outputs found

    NURBS based B-rep models for macromolecules and their properties

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    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•

    Interactive ray tracing of solvent excluded surfaces

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    Domain experts in fields concerned with the behavior of molecules, for example biochemists, employ simulations to study a moleculeโ€™s individual properties and mutual interactions with other molecules. To obtain an intuitive spatial understanding of the returned data of the simulations, various visualization techniques such as molecular surfaces can be applied on the data. The solvent excluded surface depicts the boundary between the moleculeโ€™s and a solventโ€™s occupied space and therefore the molecules accessibility for the solvent. Insight about a moleculeโ€™s potential for interaction such as reactions can be gained by studying the surfaceโ€™s shape visually. Current implementations for the visualization of the surface usually utilize GPU ray casting to achieve the performance required to allow interactivity such as viewpoint changing. However, this makes implementation of physically motivated effects like ambient occlusion or global illumination difficult. If compute resources do not contain GPUs, which is often the case in compute clusters, expensive software rasterization has to be employed instead. As CPUs offer less parallelism compared to GPUs, overhead introduced by the overdraw of thousands of primitives should be avoided. To mitigate these issues, CPU visualization approaches resurfaced again in recent times. In this work, the solvent excluded surface is visualized interactively using the classic ray tracing approach within the OSPRay CPU ray tracing framework. The described implementation is able to compute and visualize the solvent excluded surface for datasets composed of millions of atoms. Additionally, the surface supports transparency rendering, which allows implementation of a cavity visualization method that uses ambient occlusion

    Flickering nanometre-scale disorder in a crystal lattice tracked by plasmonic flare light emission

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    Abstract: The dynamic restructuring of metal nanoparticle surfaces is known to greatly influence their catalytic, electronic transport, and chemical binding functionalities. Here we show for the first time that non-equilibrium atomic-scale lattice defects can be detected in nanoparticles by purely optical means. These fluctuating states determine interface electronic transport for molecular electronics but because such rearrangements are low energy, measuring their rapid dynamics on single nanostructures by X-rays, electron beams, or tunnelling microscopies, is invasive and damaging. We utilise nano-optics at the sub-5nm scale to reveal rapid (on the millisecond timescale) evolution of defect morphologies on facets of gold nanoparticles on a mirror. Besides dynamic structural information, this highlights fundamental questions about defining bulk plasma frequencies for metals probed at the nanoscale

    Efficient numerical algorithms for surface formulations of mathematical models for biomolecule analysis and design

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 179-183).This thesis presents a set of numerical techniques that extend and improve computational modeling approaches for biomolecule analysis and design. The presented research focuses on surface formulations of modeling problems related to the estimation of the energetic cost to transfer a biomolecule from the gas phase to aqueous solution. The thesis discusses four contributions to modeling biomolecular interactions. First, the thesis presents an approach to allow accurate discretization of the most prevalent mathematical definitions of the biomolecule-solvent interface; also presented are a number of accurate techniques for numerically integrating possibly singular functions over the discretized surfaces. Such techniques are essential for solving surface formulations numerically. The second part of the thesis presents a fast multiscale numerical algorithm, FFTSVD, that efficiently solves large boundary-element method problems in biomolecule electrostatics. The algorithm synthesizes elements of other popular fast algorithms to achieve excellent efficiency and flexibility. The third thesis component describes an integral-equation formulation and boundary-element method implementation for biomolecule electrostatic analysis.(cont.) The formulation and implementation allow the solution of complicated molecular topologies and physical models. Furthermore, by applying the methods developed in the first half of the thesis, the implementation can deliver superior accuracy for competitive performance. Finally, the thesis describes a highly efficient numerical method for calculating a biomolecular charge distribution that minimizes the free energy' change of binding to another molecule. The approach, which represents a novel PDE-constrained methodology, builds on well-developed physical theory. Computational results illustrate not only the method's improved performance but also its application to realistic biomolecule problems.by Jaydeep Porter Bardhan.Ph.D

    Improvement of the survival in the seven-band grouper Epinephelus septemfasciatus larvae by optimizing aeration and water inlet in the mass-scale rearing tank

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    The water flow in larval rearing tanks has been indicated to cause mass mortality of the seven-band grouper Epinephelus septemfasciatus larvae. Therefore, a new aerating method was tested in an actual scale intensive rearing tank (8.0 m in diameter, 1.87 m of water depth, 100 m3 of volume), in which an aerator was positioned at the center of the rearing tank surrounding cylindrical drain (1.2 m in diameter) to generate the flow field, and seven larval rearing trials were performed. The survival rate with the former aeration methods were compared, in which several aerators were located in the rearing tank. The survival rate at 10 days after hatching with the new aeration method (61.5 ยฑ 5.1%, n = 7) was approximately three times higher than the former methods (21.2 ยฑ 13.7%, n = 6). The flow environment of rearing tanks was also examined by quantifying the flow field, and the relationship between the flow field in the rearing tank, behavior of larvae and survival discussed. It was confirmed that the vertical circulating flow was observed in rearing tanks, and determined effectively the survival and the behavior of grouper larvae in patchiness

    ์ตœ๋Œ€ ์ ‘์ด‰ ํ† ๋Ÿฌ์Šค ํŒจ์น˜๋ฅผ ์ด์šฉํ•œ ํšจ์œจ์ ์ธ ๊ธฐํ•˜ํ•™์  ์•Œ๊ณ ๋ฆฌ์ฆ˜

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2021.8. ์†์ƒํ˜„.We present efficient geometric algorithms that are based upon toroidal patches. To begin with, we present to use osculating toroidal patches to approximate a regular surface and propose a reparametrization method for the approximating toroidal patches. Then, we show that the toroidal patches can approximate special kinds of freeform parametric surfaces that are built upon planar profil e curves much more effectively than general surfaces. Thanks to these precise toroidal patches, we can construct a very compact bounding volume hierarchy for a parametric surface. With the bounding volume hierarchy, we can perform fast and precise point projection, i.e., minimum distance computation from a point to the surface. Also, we can easily find binormal lines, i.e. lines that connect two geometric entities orthogonally, between toroidal patches and use them to find meaningful distance measures for parametric surfaces. We show that we can fi nd such binormal lines easily by fi nding binormal lines between circles in space. Using these fundamental toroidal geometric operations, we present an efficient minimum distance computation algorithm for solids of revolution. This algorithm accelerates the minimum distance computation 10-100 times faster than conventional method. Also, we propose an efficient Hausdorff Distance computation algorithm that is applicable to various kinds of parametric surfaces. We can fi nd the Hausdorff Distance, almost up to machine precision, without much cost increase. Even though these algorithms follow conventional frameworks in large, they exhibit much better precision and efficiency than previous methods because of the toroidal patches that we use in our hierarchy.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ํ† ๋Ÿฌ์Šค ํŒจ์น˜๋ฅผ ์ด์šฉํ•œ ํšจ์œจ์ ์ธ ๊ธฐํ•˜ํ•™์  ์•Œ๊ณ ๋ฆฌ์ฆ˜๋“ค์„ ์†Œ๊ฐœํ•œ๋‹ค. ๋จผ์ €, ์ž„์˜์˜ ์ผ๋ฐ˜์ ์ธ ์ •์น™ ๊ณก๋ฉด์„ ๊ทผ์‚ฌํ•˜๊ธฐ ์œ„ํ•ด ์ตœ๋Œ€ ์ ‘์ด‰ ํ† ๋Ÿฌ์Šค ํŒจ์น˜๋ฅผ ์‚ฌ์šฉํ•  ๊ฒƒ์„ ์ œ์•ˆํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์ •์น™ ๊ณก๋ฉด์˜ ๋ณ€์ˆ˜๋ฅผ ํ† ๋Ÿฌ์Šค ํŒจ์น˜์˜ ๋ณ€์ˆ˜๋กœ ๋ณ€ํ™˜ํ•˜๋Š” ์žฌ๋งค๊ฐœํ™” ๊ณต์‹์„ ์ œ์‹œํ•œ๋‹ค. ์ด์— ๋”ํ•ด, ํ† ๋Ÿฌ์Šค ํŒจ์น˜๊ฐ€ ํ‰๋ฉด ๊ณก์„ ์— ๊ธฐ๋ฐ˜ํ•œ ํŠน์ˆ˜ํ•œ ๊ณก๋ฉด๋“ค์„ ์ผ๋ฐ˜ ๊ณก๋ฉด๋“ค๋ณด๋‹ค ๋” ํšจ๊ณผ์ ์œผ๋กœ ๊ทผ์‚ฌํ•  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์ธ๋‹ค. ์ด๋Ÿฌํ•œ ํ† ๋Ÿฌ์Šค ํŒจ์น˜์˜ ์ •ํ™•์„ฑ ๋•๋ถ„์—, ์ž„์˜์˜ ๊ณก๋ฉด์„ ๊ฐ์‹ธ๋Š” ๊ต‰์žฅํžˆ ํšจ์œจ์ ์ธ bounding volume hierarchy๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ๋‹ค. ์ด ์ž๋ฃŒ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ณต๊ฐ„ ์ƒ์˜ ํ•œ ์ ์—์„œ ํ•ด๋‹น ๊ณก๋ฉด์œผ๋กœ์˜ ์  ํˆฌ์˜ ์—ฐ์‚ฐ์„ ๊ต‰์žฅํžˆ ๋น ๋ฅด๊ณ  ์ •ํ™•ํ•˜๊ฒŒ ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ๊ณก๋ฉด๋“ค ์‚ฌ์ด์˜ ๋‹ค์–‘ํ•œ ๊ฑฐ๋ฆฌ๋“ค์„ ์ฐพ๊ธฐ ์œ„ํ•ด ์ด ์ž๋ฃŒ ๊ตฌ์กฐ์— ์ €์žฅ๋œ ํ† ๋Ÿฌ์Šค ํŒจ์น˜๋“ค์„ ์ˆ˜์ง์œผ๋กœ ์—ฐ๊ฒฐํ•˜๋Š” binormal ์ง์„ ์„ ์ด์šฉํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ binormal ์ง์„ ์„ ํšจ์œจ์ ์œผ๋กœ ์ฐพ๊ธฐ ์œ„ํ•ด ๊ณต๊ฐ„ ์ƒ์˜ ์›๋“ค์„ ์ด์šฉํ•  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์ธ๋‹ค. ํ† ๋Ÿฌ์Šค ํŒจ์น˜๊ฐ€ ์ œ๊ณตํ•˜๋Š” ์œ„์™€ ๊ฐ™์€ ๊ธฐ์ดˆ์ ์ธ ๊ธฐํ•˜ํ•™์  ์—ฐ์‚ฐ๋“ค์„ ํ† ๋Œ€๋กœ, ํšจ์œจ์ ์ธ ํšŒ์ „์ฒด ์‚ฌ์ด์˜ ์ตœ๋‹จ ๊ฑฐ๋ฆฌ ๊ณ„์‚ฐ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์‹œํ•œ๋‹ค. ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ๊ธฐ์กด์˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋น„ํ•ด 10-100๋ฐฐ ๋น ๋ฅธ ์†๋„๋กœ ์ตœ๋‹จ ๊ฑฐ๋ฆฌ๋ฅผ ๊ณ„์‚ฐํ•œ๋‹ค. ๋˜ํ•œ, ํšจ์œจ์ ์ธ ํ•˜์šฐ์Šค๋„๋ฅดํ”„ ๊ฑฐ๋ฆฌ ๊ณ„์‚ฐ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์—ญ์‹œ ์ œ์•ˆํ•œ๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ, ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ†ตํ•ด ๊ฑฐ์˜ ๊ธฐ๊ณ„ ์ •ํ™•๋„ ๋‚ด์—์„œ ์ •ํ™•ํ•œ ํ•˜์šฐ์Šค๋„๋ฅดํ”„ ๊ฑฐ๋ฆฌ๋ฅผ ํฐ ๋น„์šฉ ์ฆ๊ฐ€ ์—†์ด ๊ณ„์‚ฐํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด์™€ ๊ฐ™์€ ์„ฑ๋Šฅ ํ–ฅ์ƒ์€ ๋ณธ ๋…ผ๋ฌธ์—์„œ ์‚ฌ์šฉํ•œ ํ† ๋Ÿฌ์Šค ํŒจ์น˜์˜ ์ •ํ™•์„ฑ๊ณผ ํšจ์œจ์„ฑ์— ๊ธฐ๋ฐ˜ํ•˜๊ณ  ์žˆ๋‹ค.Chapter 1 Introduction 1 1.1 Background 1 1.2 Research Objectives and Contributions 4 1.3 Thesis Organization 6 Chapter 2 Preliminaries 7 2.1 Freeform Parametric Surface 7 2.1.1 B ezier Surface 8 2.1.2 Surface of Revolution 9 2.1.3 Surface of Linear Extrusion 10 2.2 Torus 11 Chapter 3 Related Work 13 3.1 Bounding Volume Hierarchy 13 3.2 Minimum Distance Computation 15 3.3 Hausdor Distance Computation 15 Chapter 4 Bounding Volume Hierarchy 17 4.1 Construction 17 4.2 Toroidal Patch Approximation 19 4.2.1 Regular surface 19 4.2.2 Surface of Revolution 23 4.2.3 Surface of Linear Extrusion 24 4.3 Toroidal Operations 25 4.3.1 Point Projection 25 4.3.2 Binormal Computation 27 Chapter 5 Geometric Algorithms 30 5.1 Minimum distance computation for solids of revolution 30 5.1.1 General Framework 30 5.1.2 Algorithm 31 5.1.3 Experimental Results 33 5.2 Hausdor Distance computation 37 5.2.1 General Framework 37 5.2.2 Algorithm 39 5.2.3 Experimental Results 42 Chapter 6 Conculsion 50 Appendices 52 Chapter A Torus reparametrization 53 Bibliography 60 ์ดˆ๋ก 67 Acknowledgments 68์„
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