78 research outputs found

    Computing the ฮผ-bases of algebraic monoid curves and surfaces

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    The ฮผ-basis is a developing algebraic tool to study the expressions of rational curves and surfaces. It can play a bridge role between the parametric forms and implicit forms and show some advantages in implicitization, inversion formulas and singularity computation. However, it is difficult and there are few works to compute the ฮผ-basis from an implicit form. In this paper, we derive the explicit forms of ฮผ-basis for implicit monoid curves and surfaces, including the conics and quadrics which are particular cases of these entities. Additionally, we also provide the explicit form of ฮผ-basis for monoid curves and surfaces defined by any rational parametrization (not necessarily in standard proper form). Our technique is simply based on the linear coordinate transformation and standard forms of these curves and surfaces. As a practical application in numerical situation, if an exact multiple point can not be computed, we can consider the problem of computing โ€œapproximate ฮผ-basisโ€ as well as the error estimation.Agencia Estatal de Investigaciรณ

    Non-acyclicity of coset lattices and generation of finite groups

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    Designing of objects using smooth cubic splines

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    Designing of objects using smooth cubic splines

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    Classification of flexible Kokotsakis polyhedra with quadrangular base

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    A Kokotsakis polyhedron with quadrangular base is a neighborhood of a quadrilateral in a quad surface. Generically, a Kokotsakis polyhedron is rigid. In this article we classify flexible Kokotsakis polyhedra with quadrangular bases. The analysis is based on the fact that any pair of adjacent dihedral angles of a Kokotsakis polyhedron is related by a biquadratic equation. This results in a diagram of branched covers of complex projective lines by elliptic curves. A polyhedron is flexible if and only if all repeated fiber products of coverings meet in the same Riemann surface, which is then the configuration space of the polyhedron

    Doctor of Philosophy

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    dissertationVolumetric parameterization is an emerging field in computer graphics, where volumetric representations that have a semi-regular tensor-product structure are desired in applications such as three-dimensional (3D) texture mapping and physically-based simulation. At the same time, volumetric parameterization is also needed in the Isogeometric Analysis (IA) paradigm, which uses the same parametric space for representing geometry, simulation attributes and solutions. One of the main advantages of the IA framework is that the user gets feedback directly as attributes of the NURBS model representation, which can represent geometry exactly, avoiding both the need to generate a finite element mesh and the need to reverse engineer the simulation results from the finite element mesh back into the model. Research in this area has largely been concerned with issues of the quality of the analysis and simulation results assuming the existence of a high quality volumetric NURBS model that is appropriate for simulation. However, there are currently no generally applicable approaches to generating such a model or visualizing the higher order smooth isosurfaces of the simulation attributes, either as a part of current Computer Aided Design or Reverse Engineering systems and methodologies. Furthermore, even though the mesh generation pipeline is circumvented in the concept of IA, the quality of the model still significantly influences the analysis result. This work presents a pipeline to create, analyze and visualize NURBS geometries. Based on the concept of analysis-aware modeling, this work focusses in particular on methodologies to decompose a volumetric domain into simpler pieces based on appropriate midstructures by respecting other relevant interior material attributes. The domain is decomposed such that a tensor-product style parameterization can be established on the subvolumes, where the parameterization matches along subvolume boundaries. The volumetric parameterization is optimized using gradient-based nonlinear optimization algorithms and datafitting methods are introduced to fit trivariate B-splines to the parameterized subvolumes with guaranteed order of accuracy. Then, a visualization method is proposed allowing to directly inspect isosurfaces of attributes, such as the results of analysis, embedded in the NURBS geometry. Finally, the various methodologies proposed in this work are demonstrated on complex representations arising in practice and research

    ๊ธฐํ•˜ํ•™์ ์œผ๋กœ ์ •๋ฐ€ํ•œ ๋น„์„ ํ˜• ๊ตฌ์กฐ๋ฌผ์˜ ์•„์ด์†Œ-์ง€์˜ค๋ฉ”ํŠธ๋ฆญ ํ˜•์ƒ ์„ค๊ณ„ ๋ฏผ๊ฐ๋„ ํ•ด์„

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์กฐ์„ ํ•ด์–‘๊ณตํ•™๊ณผ, 2019. 2. ์กฐ์„ ํ˜ธ.In this thesis, a continuum-based analytical adjoint configuration design sensitivity analysis (DSA) method is developed for gradient-based optimal design of curved built-up structures undergoing finite deformations. First, we investigate basic invariance property of linearized strain measures of a planar Timoshenko beam model which is combined with the selective reduced integration and B-bar projection method to alleviate shear and membrane locking. For a nonlinear structural analysis, geometrically exact beam and shell structural models are basically employed. A planar Kirchhoff beam problem is solved using the rotation-free discretization capability of isogeometric analysis (IGA) due to higher order continuity of NURBS basis function whose superior per-DOF(degree-of-freedom) accuracy over the conventional finite element analysis using Hermite basis function is verified. Various inter-patch continuity conditions including rotation continuity are enforced using Lagrage multiplier and penalty methods. This formulation is combined with a phenomenological constitutive model of shape memory polymer (SMP), and shape programming and recovery processes of SMP structures are simulated. Furthermore, for shear-deformable structures, a multiplicative update of finite rotations by an exponential map of a skew-symmetric matrix is employed. A procedure of explicit parameterization of local orthonormal frames in a spatial curve is presented using the smallest rotation method within the IGA framework. In the configuration DSA, the material derivative is applied to a variational equation, and an orientation design variation of curved structure is identified as a change of embedded local orthonormal frames. In a shell model, we use a regularized variational equation with a drilling rotational DOF. The material derivative of the orthogonal transformation matrix can be evaluated at final equilibrium configuration, which enables to compute design sensitivity using the tangent stiffness at the equilibrium without further iterations. A design optimization method for a constrained structure in a curved domain is also developed, which focuses on a lattice structure design on a specified surface. We define a lattice structure and its design variables on a rectangular plane, and utilize a concept of free-form deformation and a global curve interpolation to obtain an analytical expression for the control net of the structure on curved surface. The material derivative of the analytical expression eventually leads to precise design velocity field. Using this method, the number of design variables is reduced and design parameterization becomes more straightforward. In demonstrative examples, we verify the developed analytical adjoint DSA method in beam and shell structural problems undergoing finite deformations with various kinematic and force boundary conditions. The method is also applied to practical optimal design problems of curved built-up structures. For example, we extremize auxeticity of lattice structures, and experimentally verify nearly constant negative Poisson's ratio during large tensile and compressive deformations by using the 3-D printing and optical deformation measurement technologies. Also, we architect phononic band gap structures having significantly large band gap for mitigating noise in low audible frequency ranges.๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋Œ€๋ณ€ํ˜•์„ ๊ณ ๋ คํ•œ ํœ˜์–ด์ง„ ์กฐ๋ฆฝ ๊ตฌ์กฐ๋ฌผ์˜ ์—ฐ์†์ฒด ๊ธฐ๋ฐ˜ ํ•ด์„์  ์• ์กฐ์ธ ํ˜•์ƒ ์„ค๊ณ„ ๋ฏผ๊ฐ๋„ ํ•ด์„ ๊ธฐ๋ฒ•์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ํ‰๋ฉด Timoshenko ๋น”์˜ ์„ ํ˜•ํ™”๋œ ๋ณ€ํ˜•๋ฅ ์˜ invariance ํŠน์„ฑ์„ ๊ณ ์ฐฐํ•˜์˜€๊ณ  invariant ์ •์‹ํ™”๋ฅผ ์„ ํƒ์  ์ถ•์†Œ์ ๋ถ„(selective reduced integration) ๊ธฐ๋ฒ• ๋ฐ B-bar projection ๊ธฐ๋ฒ•๊ณผ ๊ฒฐํ•ฉํ•˜์—ฌ shear ๋ฐ membrane ์ž ๊น€ ํ˜„์ƒ์„ ํ•ด์†Œํ•˜์˜€๋‹ค. ๋น„์„ ํ˜• ๊ตฌ์กฐ ๋ชจ๋ธ๋กœ์„œ ๊ธฐํ•˜ํ•™์ ์œผ๋กœ ์ •๋ฐ€ํ•œ ๋น” ๋ฐ ์‰˜ ๋ชจ๋ธ์„ ํ™œ์šฉํ•˜์˜€๋‹ค. ํ‰๋ฉด Kirchhoff ๋น” ๋ชจ๋ธ์„ NURBS ๊ธฐ์ €ํ•จ์ˆ˜์˜ ๊ณ ์ฐจ ์—ฐ์†์„ฑ์— ๋”ฐ๋ฅธ ์•„์ด์†Œ-์ง€์˜ค๋ฉ”ํŠธ๋ฆญ ํ•ด์„ ๊ธฐ๋ฐ˜ rotation-free ์ด์‚ฐํ™”๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋‹ค๋ฃจ์—ˆ์œผ๋ฉฐ, ๊ธฐ์กด์˜ Hermite ๊ธฐ์ €ํ•จ์ˆ˜ ๊ธฐ๋ฐ˜์˜ ์œ ํ•œ์š”์†Œ๋ฒ•์— ๋น„ํ•ด ์ž์œ ๋„๋‹น ํ•ด์˜ ์ •ํ™•๋„๊ฐ€ ๋†’์Œ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ๋ผ๊ทธ๋ž‘์ง€ ์Šน์ˆ˜๋ฒ• ๋ฐ ๋ฒŒ์น™ ๊ธฐ๋ฒ•์„ ๋„์ž…ํ•˜์—ฌ ํšŒ์ „์˜ ์—ฐ์†์„ฑ์„ ํฌํ•จํ•œ ๋‹ค์–‘ํ•œ ๋‹ค์ค‘ํŒจ์น˜๊ฐ„ ์—ฐ์† ์กฐ๊ฑด์„ ๊ณ ๋ คํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ธฐ๋ฒ•์„ ํ˜„์ƒํ•™์  (phenomenological) ํ˜•์ƒ๊ธฐ์–ตํด๋ฆฌ๋จธ (SMP) ์žฌ๋ฃŒ ๊ตฌ์„ฑ๋ฐฉ์ •์‹๊ณผ ๊ฒฐํ•ฉํ•˜์—ฌ ํ˜•์ƒ์˜ ํ”„๋กœ๊ทธ๋ž˜๋ฐ๊ณผ ํšŒ๋ณต ๊ณผ์ •์„ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ํ•˜์˜€๋‹ค. ์ „๋‹จ๋ณ€ํ˜•์„ ๊ฒช๋Š” (shear-deformable) ๊ตฌ์กฐ ๋ชจ๋ธ์— ๋Œ€ํ•˜์—ฌ ๋Œ€ํšŒ์ „์˜ ๊ฐฑ์‹ ์„ ๊ต๋Œ€ ํ–‰๋ ฌ์˜ exponential map์— ์˜ํ•œ ๊ณฑ์˜ ํ˜•ํƒœ๋กœ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ณต๊ฐ„์ƒ์˜ ๊ณก์„  ๋ชจ๋ธ์—์„œ ์ตœ์†ŒํšŒ์ „ (smallest rotation) ๊ธฐ๋ฒ•์„ ํ†ตํ•ด ๊ตญ์†Œ ์ •๊ทœ์ง๊ต์ขŒํ‘œ๊ณ„์˜ ๋ช…์‹œ์  ๋งค๊ฐœํ™”๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ํ˜•์ƒ ์„ค๊ณ„ ๋ฏผ๊ฐ๋„ ํ•ด์„์„ ์œ„ํ•˜์—ฌ ์ „๋ฏธ๋ถ„์„ ๋ณ€๋ถ„ ๋ฐฉ์ •์‹์— ์ ์šฉํ•˜์˜€์œผ๋ฉฐ ํœ˜์–ด์ง„ ๊ตฌ์กฐ๋ฌผ์˜ ๋ฐฐํ–ฅ ์„ค๊ณ„ ๋ณ€ํ™”๋Š” ๊ตญ์†Œ ์ •๊ทœ์ง๊ต์ขŒํ‘œ๊ณ„์˜ ํšŒ์ „์— ์˜ํ•˜์—ฌ ๊ธฐ์ˆ ๋œ๋‹ค. ์ตœ์ข… ๋ณ€ํ˜• ํ˜•์ƒ์—์„œ ์ง๊ต ๋ณ€ํ™˜ ํ–‰๋ ฌ์˜ ์ „๋ฏธ๋ถ„์„ ๊ณ„์‚ฐํ•จ์œผ๋กœ์จ ๋Œ€ํšŒ์ „ ๋ฌธ์ œ์—์„œ ์ถ”๊ฐ€์ ์ธ ๋ฐ˜๋ณต ๊ณ„์‚ฐ์—†์ด ๋ณ€ํ˜• ํ•ด์„์—์„œ์˜ ์ ‘์„ ๊ฐ•์„ฑํ–‰๋ ฌ์— ์˜ํ•ด ํ•ด์„์  ์„ค๊ณ„ ๋ฏผ๊ฐ๋„๋ฅผ ๊ณ„์‚ฐํ•  ์ˆ˜ ์žˆ๋‹ค. ์‰˜ ๊ตฌ์กฐ๋ฌผ์˜ ๊ฒฝ์šฐ ๋ฉด๋‚ด ํšŒ์ „ ์ž์œ ๋„ ๋ฐ ์•ˆ์ •ํ™”๋œ ๋ณ€๋ถ„ ๋ฐฉ์ •์‹์„ ํ™œ์šฉํ•˜์—ฌ ๋ณด๊ฐ•์žฌ(stiffener)์˜ ๋ชจ๋ธ๋ง์„ ์šฉ์ดํ•˜๊ฒŒ ํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํœ˜์–ด์ง„ ์˜์—ญ์— ๊ตฌ์†๋˜์–ด์žˆ๋Š” ๊ตฌ์กฐ๋ฌผ์— ๋Œ€ํ•œ ์„ค๊ณ„ ์†๋„์žฅ ๊ณ„์‚ฐ ๋ฐ ์ตœ์  ์„ค๊ณ„๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•˜๋ฉฐ ํŠนํžˆ ๊ณก๋ฉด์— ๊ตฌ์†๋œ ๋น” ๊ตฌ์กฐ๋ฌผ์˜ ์„ค๊ณ„๋ฅผ ์ง‘์ค‘์ ์œผ๋กœ ๋‹ค๋ฃฌ๋‹ค. ์ž์œ ํ˜•์ƒ๋ณ€ํ˜•(Free-form deformation)๊ธฐ๋ฒ•๊ณผ ์ „์—ญ ๊ณก์„  ๋ณด๊ฐ„๊ธฐ๋ฒ•์„ ํ™œ์šฉํ•˜์—ฌ ์ง์‚ฌ๊ฐ ํ‰๋ฉด์—์„œ ํ˜•์ƒ ๋ฐ ์„ค๊ณ„ ๋ณ€์ˆ˜๋ฅผ ์ •์˜ํ•˜๊ณ  ๊ณก๋ฉด์ƒ์˜ ๊ณก์„  ํ˜•์ƒ์„ ๋‚˜ํƒ€๋‚ด๋Š” ์กฐ์ •์  ์œ„์น˜๋ฅผ ํ•ด์„์ ์œผ๋กœ ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ ์ด์˜ ์ „๋ฏธ๋ถ„์„ ํ†ตํ•ด ์ •ํ™•ํ•œ ์„ค๊ณ„์†๋„์žฅ์„ ๊ณ„์‚ฐํ•œ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์„ค๊ณ„ ๋ณ€์ˆ˜์˜ ๊ฐœ์ˆ˜๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ๊ณ  ์„ค๊ณ„์˜ ๋งค๊ฐœํ™”๊ฐ€ ๊ฐ„ํŽธํ•ด์ง„๋‹ค. ๊ฐœ๋ฐœ๋œ ๋ฐฉ๋ฒ•๋ก ์€ ๋‹ค์–‘ํ•œ ํ•˜์ค‘ ๋ฐ ์šด๋™ํ•™์  ๊ฒฝ๊ณ„์กฐ๊ฑด์„ ๊ฐ–๋Š” ๋น”๊ณผ ์‰˜์˜ ๋Œ€๋ณ€ํ˜• ๋ฌธ์ œ๋ฅผ ํ†ตํ•ด ๊ฒ€์ฆ๋˜๋ฉฐ ์—ฌ๋Ÿฌ๊ฐ€์ง€ ํœ˜์–ด์ง„ ์กฐ๋ฆฝ ๊ตฌ์กฐ๋ฌผ์˜ ์ตœ์  ์„ค๊ณ„์— ์ ์šฉ๋œ๋‹ค. ๋Œ€ํ‘œ์ ์œผ๋กœ, ์ „๋‹จ ๊ฐ•์„ฑ ๋ฐ ์ถฉ๊ฒฉ ํก์ˆ˜ ํŠน์„ฑ๊ณผ ๊ฐ™์€ ๊ธฐ๊ณ„์  ๋ฌผ์„ฑ์น˜์˜ ๊ฐœ์„ ์„ ์œ„ํ•ด ํ™œ์šฉ๋˜๋Š” ์˜ค๊ทธ์ œํ‹ฑ (auxetic) ํŠน์„ฑ์ด ๊ทน๋Œ€ํ™”๋œ ๊ฒฉ์ž ๊ตฌ์กฐ๋ฅผ ์„ค๊ณ„ํ•˜๋ฉฐ ์ธ์žฅ ๋ฐ ์••์ถ• ๋Œ€๋ณ€ํ˜• ๋ชจ๋‘์—์„œ ์ผ์ •ํ•œ ์Œ์˜ ํฌ์•„์†ก๋น„๋ฅผ ๋‚˜ํƒ€๋ƒ„์„ 3์ฐจ์› ํ”„๋ฆฐํŒ…๊ณผ ๊ด‘ํ•™์  ๋ณ€ํ˜• ์ธก์ • ๊ธฐ์ˆ ์„ ์ด์šฉํ•˜์—ฌ ์‹คํ—˜์ ์œผ๋กœ ๊ฒ€์ฆํ•œ๋‹ค. ๋˜ํ•œ ์šฐ๋ฆฌ๋Š” ์†Œ์Œ์˜ ์ €๊ฐ์„ ์œ„ํ•ด ํ™œ์šฉ๋˜๋Š” ๊ฐ€์ฒญ ์ €์ฃผํŒŒ์ˆ˜ ์˜์—ญ๋Œ€์—์„œ์˜ ๋ฐด๋“œ๊ฐญ์ด ๊ทน๋Œ€ํ™”๋œ ๊ฒฉ์ž ๊ตฌ์กฐ๋ฅผ ์ œ์‹œํ•œ๋‹ค.Abstract 1. Introduction 2. Isogeometric analysis of geometrically exact nonlinear structures 3. Isogeometric confinguration DSA of geometrically exact nonlinear structures 4. Numerical examples 5. Conclusions and future works A. Supplements to the geometrically exact Kirchhoff beam model B. Supplements to the geometrically exact shear-deformable beam model C. Supplements to the geometrically exact shear-deformable shell model D. Supplements to the invariant formulations E. Supplements to the geometric constraints in design optimization F. Supplements to the design of auxetic structures ์ดˆ๋กDocto

    Advances in Discrete Differential Geometry

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    Differential Geometr

    Advances in Discrete Differential Geometry

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    Differential Geometr

    Q(sqrt(-3))-Integral Points on a Mordell Curve

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    We use an extension of quadratic Chabauty to number fields,recently developed by the author with Balakrishnan, Besser and M ฬˆuller,combined with a sieving technique, to determine the integral points overQ(โˆšโˆ’3) on the Mordell curve y2 = x3 โˆ’ 4
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