Columnar jointing is a fracture pattern, best known from locations such as the Giant's Causeway, or Fingal's Cave, in which cracks self-organize into a nearly hexagonal arrangement, leaving behind an ordered colonnade. In this thesis observations of columnar jointing are reported from both a controlled laboratory setting, and in cooled lava flows. Experiments were performed in slurries of corn starch and water, which form columnar joints when dried. This drying process is examined in detail, and it is shown how desiccation leads to the propagation of a sharp shrinkage front. In general, but with some significant exceptions, the size of columnar joints is inversely dependent on the speed of this shrinkage front during their formation. The exceptions, which include sudden jumps in column scale, show that hysteresis is also important in choosing the column scale. Novel observations of the 3D structure of joints in starch show that columnar joints do not settle down to a perfect hexagonal pattern, but rather mature into a continuously evolving dynamic pattern. This pattern is scale invariant, and the same statistical distribution of column shapes applies equally to joints in both starch and lava. Field work was performed to study columnar jointing in the basalts of the Columbia River Basalt Group and the island of Staffa, and the more heterogeneous lava flows of Southwestern British Columbia. The widths of columns and the heights of striae (chisel-like markings that record details of cooling) were examined in detail, and these length scales are shown to be inversely proportional to each other. An additional length scale, that of wavy columns, is also first reported here. Based on these measurements, empirical advective-diffusive models are developed to describe the transport of water in a drying starch-cake, and the transport of heat in a cooling lava flow. These models have only a single scaling parameter, the Péclet number, which relates the fracture front velocity times the column size to the (thermal or hydraulic) diffusivity. In both cases, the formation of columnar joints occurs at a Péclet number of about 0.2. This model explains the hundred-fold differences in scale between columnar joints in starches and lavas, and can be used as a tool for the interpretation of joint patterns in the field.

By growing together in dense communities, microorganisms (microbes) have a huge impact on human life. Microbes also come in a wide variety of shapes, but we have yet to understand the importance of these shapes for community biology. How are multi- species communities, such as biofilms and colonies, affected by the morphologies of constituent cells? Which morphologies might these environments select for in turn? To address these questions, we use individual-based modelling to investigate the effects of cell shape on patterning and evolution within microbial communities. We develop a flexible simulation framework, coupling a continuum model of the biofilm chemical environment to a cellular-level description of biofilm growth mechanics. This modelling system allows competitions between different microbial cell shapes to be simulated and studied, in different community contexts. Our models predict that cell shape can strongly affect spatial structure and patterning within competitive communities. Rod cells perform better at colonising surfaces and the expanding edges of colonies, while round cells are better at dominating the upper surface of a community. Our predictions are supported by experiments using Escherichia coli and Pseudomonas aeruginosa bacteria, and demonstrate that particular shapes can confer a selective advantage in communities. In summary, the work presented in this thesis predicts and examines new mechanisms of self-organisation driven by cell shape, demonstrating a new significance for microbial morphology as a means for cells to succeed in a dense and competitive environment.

No description available.

The Turing mechanism for the production of a broken spatial symmetry in an initially homogeneous system of reacting and diffusing substances has attracted much interest as a potential model for certain aspects of morphogenesis such as pre-patterning in the embryo, and has also served as a model for self-organization in more generic systems. The two features necessary for the formation of Turing patterns are short-range autocatalysis and long-range inhibition which usually only occur when the diffusion rate of the inhibitor is significantly greater than that of the activator. This observation has sometimes been used to cast doubt on applicability of the Turing mechanism to cellular patterning since many messenger molecules that diffuse between cells do so at more-or-less similar rates. Here we show that stationary, symmetry-breaking Turing patterns can form in physiologically realistic systems even when the extracellular diffusion coefficients are equal; the kinetic properties of the 'receiver' and 'transmitter' proteins responsible for signal transduction will be primary factors governing this process.

We propose a dynamical systems approach to the study of weak turbulence(spatiotemporal chaos) based on the periodic orbit theory, emphasizing the role of recurrent patterns and coherent structures. After a brief review of the periodic orbit theory and its application to low-dimensional dynamics, we discuss its possible extension to study dynamics of spatially extended systems. The discussion is three-fold. First, we introduce a novel variational scheme for finding periodic orbits in high-dimensional systems. Second, we prove rigorously the existence of periodic structures (modulated amplitude waves) near the first instability of the complex Ginzburg-Landau equation, and check their role in pattern formation. Third, we present the extensive numerical exploration of the Kuramoto-Sivashinsky system in the chaotic regime: structure of the equilibrium solutions, our search for the shortest periodic orbits, description of the chaotic invariant set in terms of intrinsic coordinates and return maps on the Poincare section.

Thesis (Ph. D.)--University of Chicago, Department of Physics, December 2003. / CD-ROM contains entire thesis in PDF format. Includes bibliographical references. Also available on the Internet.

The recent success in economical production of US shales and other low permeability reservoirs is primarily due to advances in hydraulic fracturing. In this well stimulation technique, a fracturing fluid is injected into the reservoir at pressures high enough to break down the reservoir rock and form fractures. The fractures drain the hydrocarbons in the rock matrix and provide connected pathways for the transport of hydrocarbons to the wellbore. Given the low permeability of the matrix, recent studies of shale gas production suggest that nearly all of the production has to come from a ramified, well-connected network of fractures. A recent study has shown, however, that for reasons yet unknown, the production history of more than 8000 wells in the Barnett Shale can be fit with reasonable accuracy with a linear flow model based on parallel planar hydraulic fractures perpendicular to the wellbore and spaced 1-2 meters apart. The current study is carried out to provide insights into the formation and production properties of complex hydraulic fracture networks. The end goal here is optimization of hydraulic fracture treatments: creating better-connected, more productive fracture networks that can drain the reservoir more quickly. The study provides a mechanistic model of how complexity can emerge in the pattern of hydraulic fracture networks, and describes production from such networks. Invasion percolation has been used in this study to model how the pattern of hydraulic fracture networks develop. The algorithm was chosen because it allows quick testing of different “what if” scenarios while avoiding the high computation cost associated with numerical methods such as the finite element method. The rules that govern the invasion are based on a proposed geo-mechanical model of hydraulic fracture-natural fracture interactions. In the geo-mechanical model, development of fracture networks is modeled as a sequence of basic geo-mechanical events that take place as hydraulic fractures grow and interact with natural fractures. Analytical estimates are provided to predict the occurrence of each event. A complex network of connected fractures is the output of the invasion percolation algorithm and the geo-mechanical model. To predict gas production from the network, this study uses a random walk algorithm. The random walk algorithm was chosen over other numerical methods because of its advantage in handling the complex boundary conditions present in the problem, simplicity, accuracy and speed. / text

Through flume experiments we demonstrate the calcite precipitation process seen at geothermal hot springs in the lab setting. A series of four experiments were run, varying temperature and terrace ridge height while all other experimental parameters, including initial substrate slope, spring water discharge, and CO₂ input were kept constant. The goal of the experiments was to measure the temperature and terrace height control quantitatively in terms of the amount of overall travertine aggradation, aggradation rate changes in time and downstream direction, as well as to observe the effect of these parameters on processes occurring during precipitation. Using the final deposit thickness measured manually at the end of each experiment and elevation data obtained from a laser topographic profiler, I conclude that high temperature and small terrace heights favor increased precipitation of travertine. However, the amount of precipitation also depends on location within a terrace pond. Flow velocity increases as it approaches a terrace lip, resulting in enhanced precipitation and greater thicknesses in the downstream direction through increased CO₂ degassing, a process called downstream coarsening. / text

The development of spatial structure and form on vertebrate skin is a complex and poorly understood phenomenon. We consider here a new mechanochemical tissue interaction model for generating vertebrate skin patterns. Tissue interaction, which plays a crucial role in vertebrate skin morphogenesis, is modelled by reacting and diffusing signal morphogens. The model consists of seven coupled partial differential equations, one each for dermal and epidermal cell densities, four for the signal morphogen concentrations and one for describing epithelial mechanics. Because of its complexity, we reduce the full model to a small strain quasi-steady-state model, by making several simplifying assumptions. A steady state analysis demonstrates that our reduced system possesses stable time-independent steady state solutions on one-dimensional spatial domains. A linear analysis combined with a multiple time-scale perturbation procedure and numerical simulations are used to examine the range of patterns that the model can exhibit on both one- and two-dimensions domains. Spatial patterns, such as rolls, squares, rhombi and hexagons, which are remarkably similar to those observed on vertebrate skin, are obtained. Although much of the work on pattern formation is concerned with synchronous spatial patterning, many structures on vertebrate skin are laid down in a sequential fashion. Our tissue interaction model can account for such sequential pattern formation. A linear analysis and a regular perturbation analysis is used to examine propagating epithelial contraction waves coupled to dermal cell invasion waves. The results compare favourably with those obtained from numerical simulations of the model. Furthermore, sequential pattern formation on one-dimensional domains is analysed; first by an asymptotic technique, and then by a new method involving the envelopes of the spatio-temporal propagating solutions. Both methods provide analytical estimates for the speeds of the wave of propagating pattern which are in close agreement with those obtained numerically. Finally, by numerical simulations, we show that our tissue interaction model can account for two-dimensional sequential pattern formation. In particular, we show that complex two-dimensional patterns can be determined by simple quasi-one-dimensional patterns.

Columnar jointing is a fracture pattern, best known from locations such as the Giant's Causeway, or Fingal's Cave, in which cracks self-organize into a nearly hexagonal arrangement, leaving behind an ordered colonnade. In this thesis observations of columnar jointing are reported from both a controlled laboratory setting, and in cooled lava flows. Experiments were performed in slurries of corn starch and water, which form columnar joints when dried. This drying process is examined in detail, and it is shown how desiccation leads to the propagation of a sharp shrinkage front. In general, but with some significant exceptions, the size of columnar joints is inversely dependent on the speed of this shrinkage front during their formation. The exceptions, which include sudden jumps in column scale, show that hysteresis is also important in choosing the column scale. Novel observations of the 3D structure of joints in starch show that columnar joints do not settle down to a perfect hexagonal pattern, but rather mature into a continuously evolving dynamic pattern. This pattern is scale invariant, and the same statistical distribution of column shapes applies equally to joints in both starch and lava. Field work was performed to study columnar jointing in the basalts of the Columbia River Basalt Group and the island of Staffa, and the more heterogeneous lava flows of Southwestern British Columbia. The widths of columns and the heights of striae (chisel-like markings that record details of cooling) were examined in detail, and these length scales are shown to be inversely proportional to each other. An additional length scale, that of wavy columns, is also first reported here. Based on these measurements, empirical advective-diffusive models are developed to describe the transport of water in a drying starch-cake, and the transport of heat in a cooling lava flow. These models have only a single scaling parameter, the Péclet number, which relates the fracture front velocity times the column size to the (thermal or hydraulic) diffusivity. In both cases, the formation of columnar joints occurs at a Péclet number of about 0.2. This model explains the hundred-fold differences in scale between columnar joints in starches and lavas, and can be used as a tool for the interpretation of joint patterns in the field.