Optimizing the geometrical accuracy of curvilinear meshes

This paper presents a method to generate valid high order meshes with optimized geometrical accuracy. The high order meshing procedure starts with a linear mesh, that is subsequently curved without taking care of the validity of the high order elements. An optimization procedure is then used to both untangle invalid elements and optimize the geometrical accuracy of the mesh. Standard measures of the distance between curves are considered to evaluate the geometrical accuracy in planar two-dimensional meshes, but they prove computationally too costly for optimization purposes. A fast estimate of the geometrical accuracy, based on Taylor expansions of the curves, is introduced. An unconstrained optimization procedure based on this estimate is shown to yield significant improvements in the geometrical accuracy of high order meshes, as measured by the standard Haudorff distance between the geometrical model and the mesh. Several examples illustrate the beneficial impact of this method on CFD solutions, with a particular role of the enhanced mesh boundary smoothness.Comment: Submitted to JC

Certified Approximation Algorithms for the Fermat Point and n-Ellipses

Given a set A of n points in ?^d with weight function w: A??_{> 0}, the Fermat distance function is ?(x): = ?_{a?A}w(a)?x-a?. A classic problem in facility location dating back to 1643, is to find the Fermat point x*, the point that minimizes the function ?. We consider the problem of computing a point x?* that is an ?-approximation of x* in the sense that ?x?*-x*? ?(x*) and d = 2. Finally, all our planar (d = 2) algorithms are implemented in order to experimentally evaluate them, using both synthetic as well as real world datasets. These experiments show the practicality of our techniques

Rods and Rings: Soft Subdivision Planner for R^3 x S^2

We consider path planning for a rigid spatial robot moving amidst polyhedral obstacles. Our robot is either a rod or a ring. Being axially-symmetric, their configuration space is R^3 x S^2 with 5 degrees of freedom (DOF). Correct, complete and practical path planning for such robots is a long standing challenge in robotics. While the rod is one of the most widely studied spatial robots in path planning, the ring seems to be new, and a rare example of a non-simply-connected robot. This work provides rigorous and complete algorithms for these robots with theoretical guarantees. We implemented the algorithms in our open-source Core Library. Experiments show that they are practical, achieving near real-time performance. We compared our planner to state-of-the-art sampling planners in OMPL [Sucan et al., 2012]. Our subdivision path planner is based on the twin foundations of epsilon-exactness and soft predicates. Correct implementation is relatively easy. The technical innovations include subdivision atlases for S^2, introduction of Sigma_2 representations for footprints, and extensions of our feature-based technique for "opening up the blackbox of collision detection"

Doctor of Philosophy

dissertationOne of the fundamental building blocks of many computational sciences is the construction and use of a discretized, geometric representation of a problem domain, often referred to as a mesh. Such a discretization enables an otherwise complex domain to be represented simply, and computation to be performed over that domain with a finite number of basis elements. As mesh generation techniques have become more sophisticated over the years, focus has largely shifted to quality mesh generation techniques that guarantee or empirically generate numerically well-behaved elements. In this dissertation, the two complementary meshing subproblems of vertex placement and element creation are analyzed, both separately and together. First, a dynamic particle system achieves adaptivity over domains by inferring feature size through a new information passing algorithm. Second, a new tetrahedral algorithm is constructed that carefully combines lattice-based stenciling and mesh warping to produce guaranteed quality meshes on multimaterial volumetric domains. Finally, the ideas of lattice cleaving and dynamic particle systems are merged into a unified framework for producing guaranteed quality, unstructured and adaptive meshing of multimaterial volumetric domains

Voronoi diagram of orthogonal polyhedra in two and three dimensions

Τα διαγράμματα Voronoi αποτελούν μία θεμελιώδη γεωμετρική δομή δεδομένων και έκφραζουν αποστάσεις σημείων στο χώρο από ένα σύνολο αντικειμένων. Θεωρούμε ορθογώνια πολύεδρα ευθυγραμμισμένα με τους άξονες. Πρόκειται για πολύεδρα των οποίων οι έδρες σχηματίζουν ορθές γωνίες, και οι ακμές είναι παράλληλες προς τους άξονες ενός καρτεσιανού συστήματος συντεταγμένων. Κατασκευάζουμε το διάγραμμα Voronoi στο εσωτερικό ενός ορθογώνιου πολυέδρου με τρύπες που ορίζονται από αντίστοιχα πολύεδρα, χρησιμοποιώντας την max-νόρμα. Πρόκειται για έναν συνδυασμό που βρίσκει πολλές εφαρμογές σε τομείς όπως τα raster graphics και ο σχεδιασμός κυκλωμάτων VLSI. Παρουσιάζουμε έναν αλγόριθμο για την κατασκευή αυτών των διαγραμμάτων Voronoi σε δύο και τρεις διαστάσεις. Ακολουθούμε τη μέθοδο υποδιαίρεσης και βασιζόμαστε σε μία δομή δεδομένων από bounding-volumes: πρόκειται για μία μή τετριμμένη προσέγγιση του προβλήματος. Επιπλέον αναλύουμε την πολυπλοκότητα του αλγορίθμου, η οποία είναι γραμμική κάτω από μία υπόθεση ομοιόμορφα κατανεμημένης εισόδου. Μέρος της παρούσας εργασίας πρόκειται να δημοσιευθεί στα πρακτικά του συνεδρίου SEA^2 2019 (Special Event on Analysis of Experimental Algorithms).Voronoi diagrams are a fundamental geometric data structure for obtaining proximity relations. We consider axis-aligned orthogonal polyhedra in two and three-dimensional space. These are polyhedra whose faces meet at right angles and their edges are aligned with the axes of a coordinate system. We construct the exact Voronoi diagram inside an axis-aligned orthogonal polyhedron with holes defined by such polyhedra, under the max-norm. This is a particularly useful scenario in certain application domains, including raster graphics and VLSI design. Our approach avoids creating full-dimensional elements on the Voronoi diagram and yields a skeletal representation of the input object, equivalent to the straight skeleton. We introduce a complete algorithm in 2D and 3D that follows the subdivision paradigm relying on a bounding-volume hierarchy; this is an original approach to the problem. The algorithm reads in a region bounding the input polyhedron and performs a recursive subdivision into cells (using quadtrees and octrees for 2D and 3D resp.). Then, a reconstruction technique is applied to produce an isomorphic representation of the Voronoi diagram. An hierarchical data structure of bounding volumes is used to accelerate the 2D algorithm for certain inputs and is necessary for the efficiency of the 3D algorithm. The complexity is adaptive and comparable to that of previous methods. Under a mild assumption it is O(n / D+1 / D^2) in 2D or O(n a ^2 / D^2+1 / D^3) in 3D, where n is the number of sites, namely edges or facets respectively, D is the maximum cell size for the subdivision to stop (and is <1 under the appropriate scaling), and a bounds vertex cardinality per facet. We also provide a numerically stable, open-source implementation in Julia, illustrating the practical nature of our algorithm. Part of the current thesis is given in the paper "Voronoi diagram of orthogonal polyhedra in two and three dimensions", co-authored with Prof. Ioannis Z. Emiris, that is about to appear in Proceedings of SEA^2 2019 (Special Event on Analysis of Experimental Algorithms)

Quad Meshing

Triangle meshes have been nearly ubiquitous in computer graphics, and a large body of data structures and geometry processing algorithms based on them has been developed in the literature. At the same time, quadrilateral meshes, especially semi-regular ones, have advantages for many applications, and significant progress was made in quadrilateral mesh generation and processing during the last several years. In this State of the Art Report, we discuss the advantages and problems of techniques operating on quadrilateral meshes, including surface analysis and mesh quality, simplification, adaptive refinement, alignment with features, parametrization, and remeshing

Soft Subdivision Motion Planning for Complex Planar Robots

The design and implementation of theoretically-sound robot motion planning algorithms is challenging. Within the framework of resolution-exact algorithms, it is possible to exploit soft predicates for collision detection. The design of soft predicates is a balancing act between easily implementable predicates and their accuracy/effectivity. In this paper, we focus on the class of planar polygonal rigid robots with arbitrarily complex geometry. We exploit the remarkable decomposability property of soft collision-detection predicates of such robots. We introduce a general technique to produce such a decomposition. If the robot is an m-gon, the complexity of this approach scales linearly in m. This contrasts with the O(m^3) complexity known for exact planners. It follows that we can now routinely produce soft predicates for any rigid polygonal robot. This results in resolution-exact planners for such robots within the general Soft Subdivision Search (SSS) framework. This is a significant advancement in the theory of sound and complete planners for planar robots. We implemented such decomposed predicates in our open-source Core Library. The experiments show that our algorithms are effective, perform in real time on non-trivial environments, and can outperform many sampling-based methods

Minkowski Sum Construction and other Applications of Arrangements of Geodesic Arcs on the Sphere

We present two exact implementations of efficient output-sensitive algorithms that compute Minkowski sums of two convex polyhedra in 3D. We do not assume general position. Namely, we handle degenerate input, and produce exact results. We provide a tight bound on the exact maximum complexity of Minkowski sums of polytopes in 3D in terms of the number of facets of the summand polytopes. The algorithms employ variants of a data structure that represents arrangements embedded on two-dimensional parametric surfaces in 3D, and they make use of many operations applied to arrangements in these representations. We have developed software components that support the arrangement data-structure variants and the operations applied to them. These software components are generic, as they can be instantiated with any number type. However, our algorithms require only (exact) rational arithmetic. These software components together with exact rational-arithmetic enable a robust, efficient, and elegant implementation of the Minkowski-sum constructions and the related applications. These software components are provided through a package of the Computational Geometry Algorithm Library (CGAL) called Arrangement_on_surface_2. We also present exact implementations of other applications that exploit arrangements of arcs of great circles embedded on the sphere. We use them as basic blocks in an exact implementation of an efficient algorithm that partitions an assembly of polyhedra in 3D with two hands using infinite translations. This application distinctly shows the importance of exact computation, as imprecise computation might result with dismissal of valid partitioning-motions.Comment: A Ph.D. thesis carried out at the Tel-Aviv university. 134 pages long. The advisor was Prof. Dan Halperi

Self Assembly Problems of Anisotropic Particles in Soft Matter.

Anisotropic building blocks assembled from colloidal particles are attractive building blocks for self-assembled materials because their complex interactions can be exploited to drive self-assembly. In this dissertation we address the self-assembly of anisotropic particles from multiple novel computational and mathematical angles. First, we accelerate algorithms for modeling systems of anisotropic particles via massively parallel GPUs. We provide a scheme for generating statistically robust pseudo-random numbers that enables GPU acceleration of Brownian and dissipative particle dynamics. We also show how rigid body integration can be accelerated on a GPU. Integrating these two algorithms into a GPU-accelerated molecular dynamics code (HOOMD-blue), make a single GPU the ideal computing environment for modeling the self-assembly of anisotropic nanoparticles. Second, we introduce a new mathematical optimization problem, filling, a hybrid of the familiar shape packing and covering problem, which can be used to model shaped particles. We study the rich mathematical structures of the solution space and provide computational methods for finding optimal solutions for polygons and convex polyhedra. We present a sequence of isosymmetric optimal filling solutions for the Platonic solids. We then consider the filling of a hyper-cone in dimensions two to eight and show the solution remains scale-invariant but dependent on dimension. Third, we study the impact of size variation, polydispersity, on the self-assembly of an anisotropic particle, the polymer-tethered nanosphere, into ordered phases. We show that the local nanoparticle packing motif, icosahedral or crystalline, determines the impact of polydispersity on energy of the system and phase transitions. We show how extensions of the Voronoi tessellation can be calculated and applied to characterize such micro-segregated phases. By applying a Voronoi tessellation, we show that properties of the individual domains can be studied as a function of system properties such as temperature and concentration. Last, we consider the thermodynamically driven self-assembly of terminal clusters of particles. We predict that clusters related to spherical codes, a mathematical sequence of points, can be synthesized via self-assembly. These anisotropic clusters can be tuned to different anisotropies via the ratio of sphere diameters and temperature. The method suggests a rich new way for assembling anisotropic building blocks.Ph.D.Applied Physics and Scientific ComputingUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91576/1/phillicl_1.pd