Methods and Distributed Software for Visualization of Cracks Propagating in Discrete Particle Systems

Scientific visualization is becoming increasingly important in analyzing and interpreting numerical and experimental data sets. Parallel computations of discrete particle systems lead to large data sets that can be produced, stored and visualized on distributed IT infrastructures. However, this leads to very complicated environments handling complex simulation and interactive visualization on the remote heterogeneous architectures. In micro-structure of continuum, broken connections between neighbouring particles can form complex cracks of unknown geometrical shape. The complex disjoint surfaces of cracks with holes and unavailability of a suitable scalar field defining the crack surfaces limit the application of the common surface extraction methods. The main visualization task is to extract the surfaces of cracks according to the connectivity of the broken connections and the geometry of the neighbouring particles. The research aims at enhancing the visualization methods of discrete particle systems and increasing speed of distributed visualization software. The dissertation consists of introduction, three main chapters and general conclusions. In the first Chapter, a literature review on visualization software, distributed environments, discrete element simulation of particle systems and crack visualization methods is presented. In the second Chapter, novel visualization methods were proposed for extraction of crack surfaces from monodispersed particle systems modelled by the discrete element method. The cell cut-based method, the Voronoi-based method and cell centre-based method explicitly define geometry of propagating cracks in fractured regions. The proposed visualization methods were implemented in the grid visualization e–service VizLitG and the distributed visualization software VisPartDEM. Partial data set transfer from the grid storage element was developed to reduce the data transfer and visualization time. In the third Chapter, the results of experimental research are presented. The performance of e-service VizLitG was evaluated in a geographically distributed grid. Different types of software were employed for data transfer in order to present the quantitative comparison. The performance of the developed visualization methods was investigated. The quantitative comparison of the execution time of local Voronoi-based method and that of global Voronoi diagrams generated by Voro++ library was presented. The accuracy of the developed methods was evaluated by computing the total depth of cuts made in particles by the extracted crack surfaces. The present research confirmed that the proposed visualization methods and the developed distributed software were capable of visualizing crack propagation modelled by the discrete element method in monodispersed particulate media

Revisiting the Cosmological Principle in a Cellular Framework

The Cosmological Principle in it's various versions states that: (i) the Galaxy does not occupy a particular position, (ii) the Universe is homogeneous and isotropic. This statement does not agree with the recent astronomical observations in the range z lower than 0.05 which are in agreement with a cellular structure of the Universe. Here we present a local analysis of the inhomogeneity of the Universe. When z is greater than 0.05 our analysis cannot be applied because the astronomical sample of galaxies here processed is not complete. The two tools of the Poisson Voronoi tessellation (PVT) and the luminosity function for galaxies allow of building a new version of the local Cosmological Principle.Comment: 25 pages, 16 figure

Stochastic generation of biologically accurate brain networks

Basic circuits, which form the building blocks of the brain, have been identiffied in recent literature. We propose to treat these basic circuits as "stochastic generators" whose instances serve to wire a portion of the mouse brain. Very much in the same manner as genes generate proteins by providing templates for their construction, we view the catalog of basic circuits as providing templates for wiring up the neurons of the brain. This thesis work involves a) deffining a framework for the stochastic generation of brain networks, b) generation of sample networks from the basic circuits, and c) visualization of the generated networks

Role of Shape in the Self-Assembly of Anisotropic Colloids.

Self-assembly is the process of spontaneous organization of a set of interacting components. We examine how particle shape drives the self-assembly of colloids in three different systems. When particles interact only via their shape, entropic crystallization can occur; we discuss a design strategy using the Voronoi tesslelation to create “Voronoi particles,” (VP) which are hard particles in the shape of Voronoi cells of their target structure. Although VP stabilize their target structure in the limit of infinite pressure, the self-assembly of the same structure at moderate pressure is not guaranteed. We find that more symmetric crystals are often preferred due to entropic contributions of several kBT from configurational degeneracies. We characterize the assembly of VP in terms of their symmetries and the complexities of the target structure and demonstrate how controlling the degeneracies through modifying shape and field-directed assembly can improve the assembly propensity. With the addition of non-adsorbing, polymers, hard colloids experience an attraction dependent on polymer concentration, the form of which is dictated by the colloid shape; we study a system of oblate, spheroidal colloids that self-assemble thread-like clusters. In both simulation and experiment the colloids condense into disordered droplets at low polymer concentrations; at higher concentrations we observe kinetic arrest into primarily linear clusters of aligned colloids. We show that the mechanical stabilty of these low-valence structures results from the anisotropic particle shape. Particle surfaces can be patterned with metal coatings, introducing enthalpic attraction between particles; we study a system of prolate spheroidal colloids, half-coated in gold. We show with experiments and computer simulations that Janus ellipsoids can self-assemble into self-limiting one-dimensional fibers with shape-memory properties, and that the fibrillar assemblies can be actuated on application of an external alternating-current electric field. Actuation of the fibers occurs through a sliding mechanism (allowed by the curved ellipsoidal surface) that permits the reversible elongation of the Janus-ellipsoid chains by ~36%. In each case, we find shape plays a critical role. By understanding and isolating its impact, we enhance shape's utility as a parameter for the design of self-assembling colloids.PhDPhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111630/1/baschult_1.pd

Décomposition volumique d'images pour l'étude de la microstructure de la neige

Les avalanches de neige sont des phénomènes naturels complexes dont l'occurrence s'explique principalement par la structure et les propriétés du manteau neigeux. Afin de mieux comprendre les évolutions de ces propriétés au cours du temps, il est important de pouvoir caractériser la microstructure de la neige, notamment en termes de grains et de ponts de glace les reliant. Dans ce contexte, l'objectif de cette thèse est la décomposition d'échantillons de neige en grains individuels à partir d'images 3-D de neige obtenues par microtomographie X. Nous présentons ici deux méthodes de décomposition utilisant des algorithmes de géométrie discrète. Sur la base des résultats de ces segmentations, certains paramètres, comme la surface spécifique et la surface spécifique de contact entre grains sont ensuite estimés sur des échantillons de neiges variées. Ces méthodes de segmentation ouvrent de nouvelles perspectives pour la caractérisation de la microstructure de la neige, de ses propriétés, ainsi que de leur évolution au cours du temps.Snow avalanches are complex natural phenomena whose occurrence is mainly due to the structure and properties of the snowpack. To better understand the evolution of these properties over time, it is important to characterize the microstructure of snow, especially in terms of grains and ice necks that connect them. In this context, the objective of this thesis is the decomposition of snow samples into individual grains from 3-D images of snow obtained by X-ray microtomography. We present two decomposition methods using algorithms of discrete geometry. Based on the results of these segmentations, some parameters such as the specific surface area and the specific contact area between grains are then estimated from samples of several snow types. These segmentation methods offer new outlooks for the characterization of the microstructure of snow, its properties, and its time evolution

Geometrical distribution of Cryptococcus neoformans mediates flower-like biofilm development

Microbial biofilms are highly structured and dynamic communities in which phenotypic diversification allows microorganisms to adapt to different environments under distinct conditions. The environmentally ubiquitous pathogen Cryptococcus neoformans colonizes many niches of the human body and implanted medical devices in the form of biofilms, an important virulence factor. A new approach was used to characterize the underlying geometrical distribution of C. neoformans cells during the adhesion stage of biofilm formation. Geometrical aspects of adhered cells were calculated from the Delaunay triangulation and Voronoi diagramobtained fromscanning electronmicroscopy images (SEM). A correlation between increased biofilm formation and higher ordering of the underlying cell distribution was found. Mature biofilm aggregates were analyzed by applying an adapted protocol developed for ultrastructure visualization of cryptococcal cells by SEM. Flower-like clusters consisting of cells embedded in a dense layer of extracellular matrix were observed as well as distinct levels of spatial organization: adhered cells, clusters of cells and community of clusters. The results add insights into yeast motility during the dispersion stage of biofilm formation. This study highlights the importance of cellular organization for biofilm growth and presents a novel application of the geometrical method of analysis

Cohesive geometry of Cryptococcus neoformans distribution mediates flower-like biofilm development

Microbial biofilms are highly structured and dynamic communities, in which phenotypic diversification allows microorganisms to adapt to different environments under distinct conditions. Biofilms are ubiquitous in nature and colonize many niches of the human body and implanted medical devices, being an important factor in Cryptococcus neoformans infections. A new approach was used to characterize the underlying geometrical distribution of C. neoformans cells during the adhesion stage of biofilm formation. Geometrical aspects of adhered cells were calculated from the Delaunay triangulations and Voronoi diagrams obtained from scanning electron microscopy images (SEM). A correlation between increased biofilm formation and higher ordering of the underlying cell distribution was found. Mature biofilm aggregates were analyzed by applying a novel protocol developed for ultrastructure visualization of cryptococcal cells by SEM. Flower-like clusters consisting of cells embedded in a dense layer of extracellular matrix were observed as well as morphotype switches related to biofilm formation and distinct levels of spatial organization: adhered cells, clusters of cells and community of clusters. The results add insights into yeast motility during the dispersion stage of biofilm formation. This work emphasizes the importance of cellular organization for biofilm growth and may represent novel approaches to establish potential targets for the inhibition and disruption of biofilms with clinical relevance

A Cosmic Watershed: the WVF Void Detection Technique

On megaparsec scales the Universe is permeated by an intricate filigree of clusters, filaments, sheets and voids, the Cosmic Web. For the understanding of its dynamical and hierarchical history it is crucial to identify objectively its complex morphological components. One of the most characteristic aspects is that of the dominant underdense Voids, the product of a hierarchical process driven by the collapse of minor voids in addition to the merging of large ones. In this study we present an objective void finder technique which involves a minimum of assumptions about the scale, structure and shape of voids. Our void finding method, the Watershed Void Finder (WVF), is based upon the Watershed Transform, a well-known technique for the segmentation of images. Importantly, the technique has the potential to trace the existing manifestations of a void hierarchy. The basic watershed transform is augmented by a variety of correction procedures to remove spurious structure resulting from sampling noise. This study contains a detailed description of the WVF. We demonstrate how it is able to trace and identify, relatively parameter free, voids and their surrounding (filamentary and planar) boundaries. We test the technique on a set of Kinematic Voronoi models, heuristic spatial models for a cellular distribution of matter. Comparison of the WVF segmentations of low noise and high noise Voronoi models with the quantitatively known spatial characteristics of the intrinsic Voronoi tessellation shows that the size and shape of the voids are succesfully retrieved. WVF manages to even reproduce the full void size distribution function.Comment: 24 pages, 15 figures, MNRAS accepted, for full resolution, see http://www.astro.rug.nl/~weygaert/tim1publication/watershed.pd

Competing Lengthscales in Colloidal Gelation with Non-Sticky Particles

Colloidal gels are widely applied in industry due to their rheological character -- no flow takes place below the yield stress. Such property enables gels to maintain uniform distribution in practical formulations; otherwise, solid components may quickly sediment without the support of gel matrix. Compared with pure gels of sticky colloids, therefore, the composites of gel and non-sticky inclusions are more commonly encountered in reality. Through numerical simulations, we investigate the gelation process in such binary composites. We find that the non-sticky particles not only confine gelation in the form of an effective volume fraction, but also introduce another lengthscale that competes with the size of growing clusters in gel. The ratio of two key lengthscales in general controls the two effects. Using different gel models, we verify such scenario within a wide range of parameter space, suggesting a potential universality in all classes of colloidal composites