Computer Construction of the Five Platonic Convexpolyhedra Using a Guiding Sphere
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Lecture 3 1 Geometry of Linear Programs
ORIE 6300 Mathematical Programming I September 2, 2014 Lecture 3 Lecturer: David P. Williamson Scribe: Divya Singhvi Last time we discussed how to take dual of an LP in two different ways. Today we will talk about the geometry of linear programs. 1 Geometry of Linear Programs First we need some definitions. Definition 1 A set S ⊆ <n is convex if 8x; y 2 S, λx + (1 − λ)y 2 S, 8λ 2 [0; 1]. Figure 1: Examples of convex and non convex sets Given a set of inequalities we define the feasible region as P = fx 2 <n : Ax ≤ bg. We say that P is a polyhedron. Which points on this figure can have the optimal value? Our intuition from last time is that Figure 2: Example of a polyhedron. \Circled" corners are feasible and \squared" are non feasible optimal solutions to linear programming problems occur at \corners" of the feasible region. What we'd like to do now is to consider formal definitions of the \corners" of the feasible region. 3-1 One idea is that a point in the polyhedron is a corner if there is some objective function that is minimized there uniquely. Definition 2 x 2 P is a vertex of P if 9c 2 <n with cT x < cT y; 8y 6= x; y 2 P . Another idea is that a point x 2 P is a corner if there are no small perturbations of x that are in P . Definition 3 Let P be a convex set in <n. Then x 2 P is an extreme point of P if x cannot be written as λy + (1 − λ)z for y; z 2 P , y; z 6= x, 0 ≤ λ ≤ 1. -
Archimedean Solids
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln MAT Exam Expository Papers Math in the Middle Institute Partnership 7-2008 Archimedean Solids Anna Anderson University of Nebraska-Lincoln Follow this and additional works at: https://digitalcommons.unl.edu/mathmidexppap Part of the Science and Mathematics Education Commons Anderson, Anna, "Archimedean Solids" (2008). MAT Exam Expository Papers. 4. https://digitalcommons.unl.edu/mathmidexppap/4 This Article is brought to you for free and open access by the Math in the Middle Institute Partnership at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in MAT Exam Expository Papers by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Archimedean Solids Anna Anderson In partial fulfillment of the requirements for the Master of Arts in Teaching with a Specialization in the Teaching of Middle Level Mathematics in the Department of Mathematics. Jim Lewis, Advisor July 2008 2 Archimedean Solids A polygon is a simple, closed, planar figure with sides formed by joining line segments, where each line segment intersects exactly two others. If all of the sides have the same length and all of the angles are congruent, the polygon is called regular. The sum of the angles of a regular polygon with n sides, where n is 3 or more, is 180° x (n – 2) degrees. If a regular polygon were connected with other regular polygons in three dimensional space, a polyhedron could be created. In geometry, a polyhedron is a three- dimensional solid which consists of a collection of polygons joined at their edges. The word polyhedron is derived from the Greek word poly (many) and the Indo-European term hedron (seat). -
Digital Geometry Processing Mesh Basics
Digital Geometry Processing Basics Mesh Basics: Definitions, Topology & Data Structures 1 © Alla Sheffer Standard Graph Definitions G = <V,E> V = vertices = {A,B,C,D,E,F,G,H,I,J,K,L} E = edges = {(A,B),(B,C),(C,D),(D,E),(E,F),(F,G), (G,H),(H,A),(A,J),(A,G),(B,J),(K,F), (C,L),(C,I),(D,I),(D,F),(F,I),(G,K), (J,L),(J,K),(K,L),(L,I)} Vertex degree (valence) = number of edges incident on vertex deg(J) = 4, deg(H) = 2 k-regular graph = graph whose vertices all have degree k Face: cycle of vertices/edges which cannot be shortened F = faces = {(A,H,G),(A,J,K,G),(B,A,J),(B,C,L,J),(C,I,L),(C,D,I), (D,E,F),(D,I,F),(L,I,F,K),(L,J,K),(K,F,G)} © Alla Sheffer Page 1 Digital Geometry Processing Basics Connectivity Graph is connected if there is a path of edges connecting every two vertices Graph is k-connected if between every two vertices there are k edge-disjoint paths Graph G’=<V’,E’> is a subgraph of graph G=<V,E> if V’ is a subset of V and E’ is the subset of E incident on V’ Connected component of a graph: maximal connected subgraph Subset V’ of V is an independent set in G if the subgraph it induces does not contain any edges of E © Alla Sheffer Graph Embedding Graph is embedded in Rd if each vertex is assigned a position in Rd Embedding in R2 Embedding in R3 © Alla Sheffer Page 2 Digital Geometry Processing Basics Planar Graphs Planar Graph Plane Graph Planar graph: graph whose vertices and edges can Straight Line Plane Graph be embedded in R2 such that its edges do not intersect Every planar graph can be drawn as a straight-line plane graph © -
A Congruence Problem for Polyhedra
A congruence problem for polyhedra Alexander Borisov, Mark Dickinson, Stuart Hastings April 18, 2007 Abstract It is well known that to determine a triangle up to congruence requires 3 measurements: three sides, two sides and the included angle, or one side and two angles. We consider various generalizations of this fact to two and three dimensions. In particular we consider the following question: given a convex polyhedron P , how many measurements are required to determine P up to congruence? We show that in general the answer is that the number of measurements required is equal to the number of edges of the polyhedron. However, for many polyhedra fewer measurements suffice; in the case of the cube we show that nine carefully chosen measurements are enough. We also prove a number of analogous results for planar polygons. In particular we describe a variety of quadrilaterals, including all rhombi and all rectangles, that can be determined up to congruence with only four measurements, and we prove the existence of n-gons requiring only n measurements. Finally, we show that one cannot do better: for any ordered set of n distinct points in the plane one needs at least n measurements to determine this set up to congruence. An appendix by David Allwright shows that the set of twelve face-diagonals of the cube fails to determine the cube up to conjugacy. Allwright gives a classification of all hexahedra with all face- diagonals of equal length. 1 Introduction We discuss a class of problems about the congruence or similarity of three dimensional polyhedra. -
Fundamental Principles Governing the Patterning of Polyhedra
FUNDAMENTAL PRINCIPLES GOVERNING THE PATTERNING OF POLYHEDRA B.G. Thomas and M.A. Hann School of Design, University of Leeds, Leeds LS2 9JT, UK. [email protected] ABSTRACT: This paper is concerned with the regular patterning (or tiling) of the five regular polyhedra (known as the Platonic solids). The symmetries of the seventeen classes of regularly repeating patterns are considered, and those pattern classes that are capable of tiling each solid are identified. Based largely on considering the symmetry characteristics of both the pattern and the solid, a first step is made towards generating a series of rules governing the regular tiling of three-dimensional objects. Key words: symmetry, tilings, polyhedra 1. INTRODUCTION A polyhedron has been defined by Coxeter as “a finite, connected set of plane polygons, such that every side of each polygon belongs also to just one other polygon, with the provision that the polygons surrounding each vertex form a single circuit” (Coxeter, 1948, p.4). The polygons that join to form polyhedra are called faces, 1 these faces meet at edges, and edges come together at vertices. The polyhedron forms a single closed surface, dissecting space into two regions, the interior, which is finite, and the exterior that is infinite (Coxeter, 1948, p.5). The regularity of polyhedra involves regular faces, equally surrounded vertices and equal solid angles (Coxeter, 1948, p.16). Under these conditions, there are nine regular polyhedra, five being the convex Platonic solids and four being the concave Kepler-Poinsot solids. The term regular polyhedron is often used to refer only to the Platonic solids (Cromwell, 1997, p.53). -
The Crystal Forms of Diamond and Their Significance
THE CRYSTAL FORMS OF DIAMOND AND THEIR SIGNIFICANCE BY SIR C. V. RAMAN AND S. RAMASESHAN (From the Department of Physics, Indian Institute of Science, Bangalore) Received for publication, June 4, 1946 CONTENTS 1. Introductory Statement. 2. General Descriptive Characters. 3~ Some Theoretical Considerations. 4. Geometric Preliminaries. 5. The Configuration of the Edges. 6. The Crystal Symmetry of Diamond. 7. Classification of the Crystal Forros. 8. The Haidinger Diamond. 9. The Triangular Twins. 10. Some Descriptive Notes. 11. The Allo- tropic Modifications of Diamond. 12. Summary. References. Plates. 1. ~NTRODUCTORY STATEMENT THE" crystallography of diamond presents problems of peculiar interest and difficulty. The material as found is usually in the form of complete crystals bounded on all sides by their natural faces, but strangely enough, these faces generally exhibit a marked curvature. The diamonds found in the State of Panna in Central India, for example, are invariably of this kind. Other diamondsJas for example a group of specimens recently acquired for our studies ffom Hyderabad (Deccan)--show both plane and curved faces in combination. Even those diamonds which at first sight seem to resemble the standard forms of geometric crystallography, such as the rhombic dodeca- hedron or the octahedron, are found on scrutiny to exhibit features which preclude such an identification. This is the case, for example, witb. the South African diamonds presented to us for the purpose of these studŸ by the De Beers Mining Corporation of Kimberley. From these facts it is evident that the crystallography of diamond stands in a class by itself apart from that of other substances and needs to be approached from a distinctive stand- point. -
15 BASIC PROPERTIES of CONVEX POLYTOPES Martin Henk, J¨Urgenrichter-Gebert, and G¨Unterm
15 BASIC PROPERTIES OF CONVEX POLYTOPES Martin Henk, J¨urgenRichter-Gebert, and G¨unterM. Ziegler INTRODUCTION Convex polytopes are fundamental geometric objects that have been investigated since antiquity. The beauty of their theory is nowadays complemented by their im- portance for many other mathematical subjects, ranging from integration theory, algebraic topology, and algebraic geometry to linear and combinatorial optimiza- tion. In this chapter we try to give a short introduction, provide a sketch of \what polytopes look like" and \how they behave," with many explicit examples, and briefly state some main results (where further details are given in subsequent chap- ters of this Handbook). We concentrate on two main topics: • Combinatorial properties: faces (vertices, edges, . , facets) of polytopes and their relations, with special treatments of the classes of low-dimensional poly- topes and of polytopes \with few vertices;" • Geometric properties: volume and surface area, mixed volumes, and quer- massintegrals, including explicit formulas for the cases of the regular simplices, cubes, and cross-polytopes. We refer to Gr¨unbaum [Gr¨u67]for a comprehensive view of polytope theory, and to Ziegler [Zie95] respectively to Gruber [Gru07] and Schneider [Sch14] for detailed treatments of the combinatorial and of the convex geometric aspects of polytope theory. 15.1 COMBINATORIAL STRUCTURE GLOSSARY d V-polytope: The convex hull of a finite set X = fx1; : : : ; xng of points in R , n n X i X P = conv(X) := λix λ1; : : : ; λn ≥ 0; λi = 1 : i=1 i=1 H-polytope: The solution set of a finite system of linear inequalities, d T P = P (A; b) := x 2 R j ai x ≤ bi for 1 ≤ i ≤ m ; with the extra condition that the set of solutions is bounded, that is, such that m×d there is a constant N such that jjxjj ≤ N holds for all x 2 P . -
Frequently Asked Questions in Polyhedral Computation
Frequently Asked Questions in Polyhedral Computation http://www.ifor.math.ethz.ch/~fukuda/polyfaq/polyfaq.html Komei Fukuda Swiss Federal Institute of Technology Lausanne and Zurich, Switzerland [email protected] Version June 18, 2004 Contents 1 What is Polyhedral Computation FAQ? 2 2 Convex Polyhedron 3 2.1 What is convex polytope/polyhedron? . 3 2.2 What are the faces of a convex polytope/polyhedron? . 3 2.3 What is the face lattice of a convex polytope . 4 2.4 What is a dual of a convex polytope? . 4 2.5 What is simplex? . 4 2.6 What is cube/hypercube/cross polytope? . 5 2.7 What is simple/simplicial polytope? . 5 2.8 What is 0-1 polytope? . 5 2.9 What is the best upper bound of the numbers of k-dimensional faces of a d- polytope with n vertices? . 5 2.10 What is convex hull? What is the convex hull problem? . 6 2.11 What is the Minkowski-Weyl theorem for convex polyhedra? . 6 2.12 What is the vertex enumeration problem, and what is the facet enumeration problem? . 7 1 2.13 How can one enumerate all faces of a convex polyhedron? . 7 2.14 What computer models are appropriate for the polyhedral computation? . 8 2.15 How do we measure the complexity of a convex hull algorithm? . 8 2.16 How many facets does the average polytope with n vertices in Rd have? . 9 2.17 How many facets can a 0-1 polytope with n vertices in Rd have? . 10 2.18 How hard is it to verify that an H-polyhedron PH and a V-polyhedron PV are equal? . -
Points, Lines, and Planes a Point Is a Position in Space. a Point Has No Length Or Width Or Thickness
Points, Lines, and Planes A Point is a position in space. A point has no length or width or thickness. A point in geometry is represented by a dot. To name a point, we usually use a (capital) letter. A A (straight) line has length but no width or thickness. A line is understood to extend indefinitely to both sides. It does not have a beginning or end. A B C D A line consists of infinitely many points. The four points A, B, C, D are all on the same line. Postulate: Two points determine a line. We name a line by using any two points on the line, so the above line can be named as any of the following: ! ! ! ! ! AB BC AC AD CD Any three or more points that are on the same line are called colinear points. In the above, points A; B; C; D are all colinear. A Ray is part of a line that has a beginning point, and extends indefinitely to one direction. A B C D A ray is named by using its beginning point with another point it contains. −! −! −−! −−! In the above, ray AB is the same ray as AC or AD. But ray BD is not the same −−! ray as AD. A (line) segment is a finite part of a line between two points, called its end points. A segment has a finite length. A B C D B C In the above, segment AD is not the same as segment BC Segment Addition Postulate: In a line segment, if points A; B; C are colinear and point B is between point A and point C, then AB + BC = AC You may look at the plus sign, +, as adding the length of the segments as numbers. -
Bridges Conference Proceedings Guidelines Word
Bridges 2019 Conference Proceedings Helixation Rinus Roelofs Lansinkweg 28, Hengelo, the Netherlands; [email protected] Abstract In the list of names of the regular and semi-regular polyhedra we find many names that refer to a process. Examples are ‘truncated’ cube and ‘stellated’ dodecahedron. And Luca Pacioli named some of his polyhedral objects ‘elevations’. This kind of name-giving makes it easier to understand these polyhedra. We can imagine the model as a result of a transformation. And nowadays we are able to visualize this process by using the technique of animation. Here I will to introduce ‘helixation’ as a process to get a better understanding of the Poinsot polyhedra. In this paper I will limit myself to uniform polyhedra. Introduction Most of the Archimedean solids can be derived by cutting away parts of a Platonic solid. This operation , with which we can generate most of the semi-regular solids, is called truncation. Figure 1: Truncation of the cube. We can truncate the vertices of a polyhedron until the original faces of the polyhedron become regular again. In Figure 1 this process is shown starting with a cube. In the third object in the row, the vertices are truncated in such a way that the square faces of the cube are transformed to regular octagons. The resulting object is the Archimedean solid, the truncated cube. We can continue the process until we reach the fifth object in the row, which again is an Archimedean solid, the cuboctahedron. The whole process or can be represented as an animation. Also elevation and stellation can be described as processes. -
Tetrahedral Decompositions of Hexahedral Meshes
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Europ. J. Combinatorics (1989) 10, 435-443 Tetrahedral Decompositions of Hexahedral Meshes DEREK HACON AND CARLOS TOMEI A hexahedral mesh is a partition of a region in 3-space 1R3 into (not necessarily regular) hexahedra which fit together face to face. We are concerned here with the question of how the hexahedra may be decomposed into tetrahedra without introducing any new vertices. We consider two possible decompositions, in which each hexahedron breaks into five or six tetrahedra in a prescribed fashion. In both cases, we obtain simple verifiable criteria for the existence of a decomposition, by making use of elementary facts of graph theory and algebraic. topology. 1. INTRODUcnON A hexahedral mesh is a partition of a region in 3-space ~3 into (not necessarily regular) hexahedra which fit together face to face. We are concerned here with the question of how the hexahedra may be decomposed into tetrahedra without introduc ing any new vertices. There is one well known [1] way of decomposing a hexahedral mesh into non-overlapping tetrahedra which always works. Start by labelling the vertices 1,2,3, .... Then divide each face into two triangles by the diagonal containing the first vertex of the face. Next consider a hexahedron H with first vertex V. The three faces of H not containing V have already been divided up into a total of six triangles, so take each of these to be the base of a tetrahedron with apex V. -
Dodecahedron
Dodecahedron Figure 1 Regular Dodecahedron vertex labeling using “120 Polyhedron” vertex labels. COPYRIGHT 2007, Robert W. Gray Page 1 of 9 Encyclopedia Polyhedra: Last Revision: July 8, 2007 DODECAHEDRON Topology: Vertices = 20 Edges = 30 Faces = 12 pentagons Lengths: 15+ ϕ = 1.618 033 989 2 EL ≡ Edge length of regular Dodecahedron. 43ϕ + FA = EL 1.538 841 769 EL ≡ Face altitude. 2 ϕ DFV = EL ≅ 0.850 650 808 EL 5 15+ 20 ϕ DFE = EL ≅ 0.688 190 960 EL 10 3 DVV = ϕ EL ≅ 1.401 258 538 EL 2 1 DVE = ϕ 2 EL ≅ 1.309 016 994 EL 2 711+ ϕ DVF = EL ≅ 1.113 516 364 EL 20 COPYRIGHT 2007, Robert W. Gray Page 2 of 9 Encyclopedia Polyhedra: Last Revision: July 8, 2007 DODECAHEDRON Areas: 15+ 20 ϕ 2 2 Area of one pentagonal face = EL ≅ 1.720 477 401 EL 4 2 2 Total face area = 31520+ ϕ EL ≅ 20.645 728 807 EL Volume: 47+ ϕ 3 3 Cubic measure volume equation = EL ≅ 7.663 118 961 EL 2 38( + 14ϕ) 3 3 Synergetics' Tetra-volume equation = EL ≅ 65.023 720 585 EL 2 Angles: Face Angles: All face angles are 108°. Sum of face angles = 6480° Central Angles: ⎛⎞35− All central angles are = 2arcsin ⎜⎟ ≅ 41.810 314 896° ⎜⎟6 ⎝⎠ Dihedral Angles: ⎛⎞2 ϕ 2 All dihedral angles are = 2arcsin ⎜⎟ ≅ 116.565 051 177° ⎝⎠43ϕ + COPYRIGHT 2007, Robert W. Gray Page 3 of 9 Encyclopedia Polyhedra: Last Revision: July 8, 2007 DODECAHEDRON Additional Angle Information: Note that Central Angle(Dodecahedron) + Dihedral Angle(Icosahedron) = 180° Central Angle(Icosahedron) + Dihedral Angle(Dodecahedron) = 180° which is the case for dual polyhedra.