Beyond Developable: Omputational Design and Fabrication with Auxetic Materials
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ICES REPORT 14-22 Characterization, Enumeration and Construction Of
ICES REPORT 14-22 August 2014 Characterization, Enumeration and Construction of Almost-regular Polyhedra by Muhibur Rasheed and Chandrajit Bajaj The Institute for Computational Engineering and Sciences The University of Texas at Austin Austin, Texas 78712 Reference: Muhibur Rasheed and Chandrajit Bajaj, "Characterization, Enumeration and Construction of Almost-regular Polyhedra," ICES REPORT 14-22, The Institute for Computational Engineering and Sciences, The University of Texas at Austin, August 2014. Characterization, Enumeration and Construction of Almost-regular Polyhedra Muhibur Rasheed and Chandrajit Bajaj Center for Computational Visualization Institute of Computational Engineering and Sciences The University of Texas at Austin Austin, Texas, USA Abstract The symmetries and properties of the 5 known regular polyhedra are well studied. These polyhedra have the highest order of 3D symmetries, making them exceptionally attractive tem- plates for (self)-assembly using minimal types of building blocks, from nanocages and virus capsids to large scale constructions like glass domes. However, the 5 polyhedra only represent a small number of possible spherical layouts which can serve as templates for symmetric assembly. In this paper, we formalize the notion of symmetric assembly, specifically for the case when only one type of building block is used, and characterize the properties of the corresponding layouts. We show that such layouts can be generated by extending the 5 regular polyhedra in a sym- metry preserving way. The resulting family remains isotoxal and isohedral, but not isogonal; hence creating a new class outside of the well-studied regular, semi-regular and quasi-regular classes and their duals Catalan solids and Johnson solids. We also show that this new family, dubbed almost-regular polyhedra, can be parameterized using only two variables and constructed efficiently. -
A Hybrid Global Optimization Method: the One-Dimensional Case Peiliang Xu
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Journal of Computational and Applied Mathematics 147 (2002) 301–314 www.elsevier.com/locate/cam A hybrid global optimization method: the one-dimensional case Peiliang Xu Disaster Prevention Research Institute, Kyoto University, Uji, Kyoto 611-0011, Japan Received 20 February 2001; received in revised form 4 February 2002 Abstract We propose a hybrid global optimization method for nonlinear inverse problems. The method consists of two components: local optimizers and feasible point ÿnders. Local optimizers have been well developed in the literature and can reliably attain the local optimal solution. The feasible point ÿnder proposed here is equivalent to ÿnding the zero points of a one-dimensional function. It warrants that local optimizers either obtain a better solution in the next iteration or produce a global optimal solution. The algorithm by assembling these two components has been proved to converge globally and is able to ÿnd all the global optimal solutions. The method has been demonstrated to perform excellently with an example having more than 1 750 000 local minima over [ −106; 107].c 2002 Elsevier Science B.V. All rights reserved. Keywords: Interval analysis; Hybrid global optimization 1. Introduction Many problems in science and engineering can ultimately be formulated as an optimization (max- imization or minimization) model. In the Earth Sciences, we have tried to collect data in a best way and then to extract the information on, for example, the Earth’s velocity structures and=or its stress=strain state, from the collected data as much as possible. -
Geometric GSI’19 Science of Information Toulouse, 27Th - 29Th August 2019
ALEAE GEOMETRIA Geometric GSI’19 Science of Information Toulouse, 27th - 29th August 2019 // Program // GSI’19 Geometric Science of Information On behalf of both the organizing and the scientific committees, it is // Welcome message our great pleasure to welcome all delegates, representatives and participants from around the world to the fourth International SEE from GSI’19 chairmen conference on “Geometric Science of Information” (GSI’19), hosted at ENAC in Toulouse, 27th to 29th August 2019. GSI’19 benefits from scientific sponsor and financial sponsors. The 3-day conference is also organized in the frame of the relations set up between SEE and scientific institutions or academic laboratories: ENAC, Institut Mathématique de Bordeaux, Ecole Polytechnique, Ecole des Mines ParisTech, INRIA, CentraleSupélec, Institut Mathématique de Bordeaux, Sony Computer Science Laboratories. We would like to express all our thanks to the local organizers (ENAC, IMT and CIMI Labex) for hosting this event at the interface between Geometry, Probability and Information Geometry. The GSI conference cycle has been initiated by the Brillouin Seminar Team as soon as 2009. The GSI’19 event has been motivated in the continuity of first initiatives launched in 2013 at Mines PatisTech, consolidated in 2015 at Ecole Polytechnique and opened to new communities in 2017 at Mines ParisTech. We mention that in 2011, we // Frank Nielsen, co-chair Ecole Polytechnique, Palaiseau, France organized an indo-french workshop on “Matrix Information Geometry” Sony Computer Science Laboratories, that yielded an edited book in 2013, and in 2017, collaborate to CIRM Tokyo, Japan seminar in Luminy TGSI’17 “Topoplogical & Geometrical Structures of Information”. -
Omputational Design and Fabrication with Auxetic Materials
Beyond Developable: Computational Design and Fabrication with Auxetic Materials Mina Konakovic´ Keenan Crane Bailin Deng Sofien Bouaziz Daniel Piker Mark Pauly EPFL CMU University of Hull EPFL EPFL Figure 1: Introducing a regular pattern of slits turns inextensible, but flexible sheet material into an auxetic material that can locally expand in an approximately uniform way. This modified deformation behavior allows the material to assume complex double-curved shapes. The shoe model has been fabricated from a single piece of metallic material using a new interactive rationalization method based on conformal geometry and global, non-linear optimization. Thanks to our global approach, the 2D layout of the material can be computed such that no discontinuities occur at the seam. The center zoom shows the region of the seam, where one row of triangles is doubled to allow for easy gluing along the boundaries. The base is 3D printed. Abstract 1 Introduction We present a computational method for interactive 3D design and Recent advances in material science and digital fabrication provide rationalization of surfaces via auxetic materials, i.e., flat flexible promising opportunities for industrial and product design, engi- material that can stretch uniformly up to a certain extent. A key neering, architecture, art and science [Caneparo 2014; Gibson et al. motivation for studying such material is that one can approximate 2015]. To bring these innovations to fruition, effective computational doubly-curved surfaces (such as the sphere) using only flat pieces, tools are needed that link creative design exploration to material making it attractive for fabrication. We physically realize surfaces realization. A versatile approach is to abstract material and fabrica- by introducing cuts into approximately inextensible material such tion constraints into suitable geometric representations which are as sheet metal, plastic, or leather. -
Arxiv:1804.07332V1 [Math.OC] 19 Apr 2018
Juniper: An Open-Source Nonlinear Branch-and-Bound Solver in Julia Ole Kr¨oger,Carleton Coffrin, Hassan Hijazi, Harsha Nagarajan Los Alamos National Laboratory, Los Alamos, New Mexico, USA Abstract. Nonconvex mixed-integer nonlinear programs (MINLPs) rep- resent a challenging class of optimization problems that often arise in engineering and scientific applications. Because of nonconvexities, these programs are typically solved with global optimization algorithms, which have limited scalability. However, nonlinear branch-and-bound has re- cently been shown to be an effective heuristic for quickly finding high- quality solutions to large-scale nonconvex MINLPs, such as those arising in infrastructure network optimization. This work proposes Juniper, a Julia-based open-source solver for nonlinear branch-and-bound. Leverag- ing the high-level Julia programming language makes it easy to modify Juniper's algorithm and explore extensions, such as branching heuris- tics, feasibility pumps, and parallelization. Detailed numerical experi- ments demonstrate that the initial release of Juniper is comparable with other nonlinear branch-and-bound solvers, such as Bonmin, Minotaur, and Knitro, illustrating that Juniper provides a strong foundation for further exploration in utilizing nonlinear branch-and-bound algorithms as heuristics for nonconvex MINLPs. 1 Introduction Many of the optimization problems arising in engineering and scientific disci- plines combine both nonlinear equations and discrete decision variables. Notable examples include the blending/pooling problem [1,2] and the design and opera- tion of power networks [3,4,5] and natural gas networks [6]. All of these problems fall into the class of mixed-integer nonlinear programs (MINLPs), namely, minimize: f(x; y) s.t. -
Generating Apparently-Random Colour Patterns
Computational Aesthetics in Graphics, Visualization, and Imaging (2012) D. Cunningham and D. House (Editors) Random Discrete Colour Sampling Henrik Lieng Christian Richardt Neil A. Dodgson Generating apparently-randomUniversity of Cambridge colour patterns Used with permission of the authors Figure 1: We present an algorithm that distributes colours randomly using a human-centric definition of randomness. Left: Colours distributed using Matlab’s random-number generator. Middle: Result of our algorithm. Notice that our algorithm does not produce any distinctive patterns. Right: An image similar to one of Damien Hirst’s spot paintings. Abstract Apparently-random distributions of colours in a discrete setting have been used by many artists and craftsmen in the past century. Manual colourisation is a tedious and difficult process. Automatic colourisation, on the other hand, tends not to not look ‘random’ to a human, as randomly-generated clusters and patterns stimulate human perception and break the appearance of randomness. We propose an algorithm that minimises these apparent patterns, making the distribution of colours look as if they have been distributed randomly by a human. We show that our approach is superior to current solutions, especially for small numbers of colours. Our algorithm is easily extendible to non-regular patterns in any coordinate system. Categories and Subject Descriptors (according to ACM CCS): I.3.8 [Computer Graphics]: Applications; I.3.m [Com- puter Graphics]: Miscellaneous—Visual Arts; J.5 [Arts and Humanities]: Fine Arts. 1. Introduction Random colour sampling in the spatially discrete space was used in the early twentieth-century by numerous artists such as Jean Arp, Sophie Tauber and Vilmos Huszár. -
Global Optimization, the Gaussian Ensemble, and Universal Ensemble Equivalence
Probability, Geometry and Integrable Systems MSRI Publications Volume 55, 2007 Global optimization, the Gaussian ensemble, and universal ensemble equivalence MARIUS COSTENIUC, RICHARD S. ELLIS, HUGO TOUCHETTE, AND BRUCE TURKINGTON With great affection this paper is dedicated to Henry McKean on the occasion of his 75th birthday. ABSTRACT. Given a constrained minimization problem, under what condi- tions does there exist a related, unconstrained problem having the same mini- mum points? This basic question in global optimization motivates this paper, which answers it from the viewpoint of statistical mechanics. In this context, it reduces to the fundamental question of the equivalence and nonequivalence of ensembles, which is analyzed using the theory of large deviations and the theory of convex functions. In a 2000 paper appearing in the Journal of Statistical Physics, we gave nec- essary and sufficient conditions for ensemble equivalence and nonequivalence in terms of support and concavity properties of the microcanonical entropy. In later research we significantly extended those results by introducing a class of Gaussian ensembles, which are obtained from the canonical ensemble by adding an exponential factor involving a quadratic function of the Hamiltonian. The present paper is an overview of our work on this topic. Our most important discovery is that even when the microcanonical and canonical ensembles are not equivalent, one can often find a Gaussian ensemble that satisfies a strong form of equivalence with the microcanonical ensemble known as universal equivalence. When translated back into optimization theory, this implies that an unconstrained minimization problem involving a Lagrange multiplier and a quadratic penalty function has the same minimum points as the original con- strained problem. -
Eindhoven University of Technology MASTER Lateral Stiffness Of
Eindhoven University of Technology MASTER Lateral stiffness of hexagrid structures de Meijer, J.H.M. Award date: 2012 Link to publication Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain ‘Lateral Stiffness of Hexagrid Structures’ - Master’s thesis – - Main report – - A 2012.03 – - O 2012.03 – J.H.M. de Meijer 0590897 July, 2012 Graduation committee: Prof. ir. H.H. Snijder (supervisor) ir. A.P.H.W. Habraken dr.ir. H. Hofmeyer Eindhoven University of Technology Department of the Built Environment Structural Design Preface This research forms the main part of my graduation thesis on the lateral stiffness of hexagrids. It explores the opportunities of a structural stability system that has been researched insufficiently. -
Couenne: a User's Manual
couenne: a user’s manual Pietro Belotti⋆ Dept. of Mathematical Sciences, Clemson University Clemson SC 29634. Abstract. This is a short user’s manual for the couenne open-source software for global optimization. It provides downloading and installation instructions, an explanation to all options available in couenne, and suggestions on when to use some of its features. 1 Introduction couenne is an Open Source code for solving Global Optimization problems, i.e., problems of the form (P) min f(x) s.t. gj(x) ≤ 0 ∀j ∈ M l u xi ≤ xi ≤ xi ∀i ∈ N0 Z I xi ∈ ∀i ∈ N0 ⊆ N0, n n where f : R → R and, for all j ∈ M, gj : R → R are multivariate (possibly nonconvex) functions, n = |N0| is the number of variables, and x = (xi)i∈N0 is the n-vector of variables. We assume that f and all gj’s are factorable, i.e., they are expressed as Ph Qk ηhk(x), where all functions ηhk(x) are univariate. couenne is part of the COIN-OR infrastructure for Operations Research software1. It is a reformulation-based spatial branch&bound (sBB) [10,11,12], and it implements: – linearization; – branching; – heuristics to find feasible solutions; – bound reduction. Its main purpose is to provide the Optimization community with an Open- Source tool that can be specialized to handle specific classes of MINLP problems, or improved by adding more efficient linearization, branching, heuristic, and bound reduction techniques. ⋆ Email: [email protected] 1 See http://www.coin-or.org Web resources. The homepage of couenne is on the COIN-OR website: http://www.coin-or.org/Couenne and shows a brief description of couenne and some useful links. -
Stochastic Optimization,” in Handbook of Computational Statistics: Concepts and Methods (2Nd Ed.) (J
Citation: Spall, J. C. (2012), “Stochastic Optimization,” in Handbook of Computational Statistics: Concepts and Methods (2nd ed.) (J. Gentle, W. Härdle, and Y. Mori, eds.), Springer−Verlag, Heidelberg, Chapter 7, pp. 173–201. dx.doi.org/10.1007/978-3-642-21551-3_7 STOCHASTIC OPTIMIZATION James C. Spall The Johns Hopkins University Applied Physics Laboratory 11100 Johns Hopkins Road Laurel, Maryland 20723-6099 U.S.A. [email protected] Stochastic optimization algorithms have been growing rapidly in popularity over the last decade or two, with a number of methods now becoming “industry standard” approaches for solving challenging optimization problems. This chapter provides a synopsis of some of the critical issues associated with stochastic optimization and a gives a summary of several popular algorithms. Much more complete discussions are available in the indicated references. To help constrain the scope of this article, we restrict our attention to methods using only measurements of the criterion (loss function). Hence, we do not cover the many stochastic methods using information such as gradients of the loss function. Section 1 discusses some general issues in stochastic optimization. Section 2 discusses random search methods, which are simple and surprisingly powerful in many applications. Section 3 discusses stochastic approximation, which is a foundational approach in stochastic optimization. Section 4 discusses a popular method that is based on connections to natural evolution—genetic algorithms. Finally, Section 5 offers some concluding remarks. 1 Introduction 1.1 General Background Stochastic optimization plays a significant role in the analysis, design, and operation of modern systems. Methods for stochastic optimization provide a means of coping with inherent system noise and coping with models or systems that are highly nonlinear, high dimensional, or otherwise inappropriate for classical deterministic methods of optimization. -
Global Optimization Methods for Chemical Process Design: Deterministic and Stochastic Approaches
Korean J. Chem. Eng., 19(2), 227-232 (2002) SHORT COMMUNICATION Global Optimization Methods for Chemical Process Design: Deterministic and Stochastic Approaches Soo Hyoung Choi† and Vasilios Manousiouthakis* School of Chemical Engineering and Technology, Chonbuk National University, Jeonju 561-756, S. Korea *Chemical Engineering Department, University of California Los Angeles, Los Angeles, CA 90095, USA (Received 24 September 2001 • accepted 22 November 2001) Abstract−Process optimization often leads to nonconvex nonlinear programming problems, which may have multiple local optima. There are two major approaches to the identification of the global optimum: deterministic approach and stochastic approach. Algorithms based on the deterministic approach guarantee the global optimality of the obtained solution, but are usually applicable to small problems only. Algorithms based on the stochastic approach, which do not guarantee the global optimality, are applicable to large problems, but inefficient when nonlinear equality con- straints are involved. This paper reviews representative deterministic and stochastic global optimization algorithms in order to evaluate their applicability to process design problems, which are generally large, and have many nonlinear equality constraints. Finally, modified stochastic methods are investigated, which use a deterministic local algorithm and a stochastic global algorithm together to be suitable for such problems. Key words: Global Optimization, Deterministic, Stochastic Approach, Nonconvex, Nonlinear -
Visualization of Regular Maps
Symmetric Tiling of Closed Surfaces: Visualization of Regular Maps Jarke J. van Wijk Dept. of Mathematics and Computer Science Technische Universiteit Eindhoven [email protected] Abstract The first puzzle is trivial: We get a cube, blown up to a sphere, which is an example of a regular map. A cube is 2×4×6 = 48-fold A regular map is a tiling of a closed surface into faces, bounded symmetric, since each triangle shown in Figure 1 can be mapped to by edges that join pairs of vertices, such that these elements exhibit another one by rotation and turning the surface inside-out. We re- a maximal symmetry. For genus 0 and 1 (spheres and tori) it is quire for all solutions that they have such a 2pF -fold symmetry. well known how to generate and present regular maps, the Platonic Puzzle 2 to 4 are not difficult, and lead to other examples: a dodec- solids are a familiar example. We present a method for the gener- ahedron; a beach ball, also known as a hosohedron [Coxeter 1989]; ation of space models of regular maps for genus 2 and higher. The and a torus, obtained by making a 6 × 6 checkerboard, followed by method is based on a generalization of the method for tori. Shapes matching opposite sides. The next puzzles are more challenging. with the proper genus are derived from regular maps by tubifica- tion: edges are replaced by tubes. Tessellations are produced us- ing group theory and hyperbolic geometry. The main results are a generic procedure to produce such tilings, and a collection of in- triguing shapes and images.