Hydrodynamic correlation functions of a driven granular fluid in steady state

We study a homogeneously driven granular fluid of hard spheres at intermediate volume fractions and focus on time-delayed correlation functions in the stationary state. Inelastic collisions are modeled by incomplete normal restitution, allowing for efficient simulations with an event-driven algorithm. The incoherent scattering function Fincoh(q,t ) is seen to follow time-density superposition with a relaxation time that increases significantly as the volume fraction increases. The statistics of particle displacements is approximately Gaussian. For the coherent scattering function S(q,ω), we compare our results to the predictions of generalized fluctuating hydrodynamics, which takes into account that temperature fluctuations decay either diffusively or with a finite relaxation rate, depending on wave number and inelasticity. For sufficiently small wave number q we observe sound waves in the coherent scattering function S(q,ω) and the longitudinal current correlation function Cl(q,ω). We determine the speed of sound and the transport coefficients and compare them to the results of kinetic theory.

Plexiform hybrid granular cell tumor/perineurioma: a novel variant of benign peripheral nerve sheath tumor with divergent differentiation

The descriptive term hybrid peripheral nerve sheath tumor refers to any neoplasm of the neurilemmal apparatus composed of more than one pathologically defined tumoral equivalent derived from its constituent cells. Within this uncommon nosological category, participation of granular cell tumor - a neoplasm of modified Schwann cells - has been reported only exceptionally. We describe a hitherto not documented variant composed of an organoid mixture of granular cell tumor and perineurioma with plexiform growth. A solitary subcutaneous nodule of 1.5 cm diameter was excised from the right ring finger of a 19-year-old female with no antecedents of neurofibromatosis or relevant trauma. Histology revealed a monotonous, yet cytologically dimorphic proliferation of classical granular cells intermingled with flattened, inconspicuous perineurial cells. Immunohistochemical double labeling detected expression of S100 protein in the former and of EMA and GLUT-1 in the latter. While the respective staining patterns for S100 protein and EMA or GLUT-1 tended to be mutually exclusive, a minority of cells exhibited transitional granular cell/perineurial immunophenotype. Electron microscopy permitted direct visualization of a plethora of lysosomes in the granular cell moiety, and of pinocytotic vesicles and tight junctions in perineurial cells. Intratumoral axons were not detected. Expanding intraneurally, the lesion showed discrete encapsulation by the local perineurium, and resulted in plexiform growth. The MIB-1 labeling index averaged 1%. We interpret our findings as supporting evidence for the dual cell lineage to have arisen through metaplasia, with the tumor's dynamics probably having been driven by the granular cell component.

Strong Dynamical Heterogeneity and Universal Scaling in Driven Granular Fluids

Large-scale simulations of two-dimensional bidisperse granular fluids allow us to determine spatial correlations of slow particles via the four-point structure factor S-4 (q, t). Both cases, elastic (epsilon = 1) and inelastic (epsilon < 1) collisions, are studied. As the fluid approaches structural arrest, i.e., for packing fractions in the range 0.6 <= phi <= 0.805, scaling is shown to hold: S-4 (q, t)/chi(4)(t) = s(q xi(t)). Both the dynamic susceptibility chi(4)(tau(alpha)) and the dynamic correlation length xi(tau(alpha)) evaluated at the alpha relaxation time tau(alpha) can be fitted to a power law divergence at a critical packing fraction. The measured xi(tau(alpha)) widely exceeds the largest one previously observed for three-dimensional (3d) hard sphere fluids. The number of particles in a slow cluster and the correlation length are related by a robust power law, chi(4)(tau(alpha)) approximate to xi(d-p) (tau(alpha)), with an exponent d - p approximate to 1.6. This scaling is remarkably independent of epsilon, even though the strength of the dynamical heterogeneity at constant volume fraction depends strongly on epsilon.

Numerical and granulometric approaches to geophysical granular flows

Volcanic ash clouds can be fed by an upward-directed eruption column (Plinian column) or by elutriation from extensive pyroclastic-flows (coignimbrite cloud). For large-scale eruptions, there is considerable uncertainty about which mechanism is dominant. Here we analyze in a novel way a comprehensive grainsize database for pyroclastic deposits. We demonstrate that the Mount Pinatubo climactic eruption deposits were substantially derived from coignimbrite clouds, and not only by a Plinian cloud as generally thought. Coignimbrite ash-fall deposits are much richer in breathable <10 m ash (5–25 wt%) than pure Plinian ash at most distances from the source volcano. We also show that coignimbrite ash clouds, as at Pinatubo, are expected to be more water rich than Plinian clouds, leading to removal of more HCl prior to stratospheric injection, thereby reducing their atmospheric impact.

Granular computing as a tool of human data interaction - a cognitive cities use case

The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.

Granular flow in polymineralic rocks bearing sheet silicates: New evidence from natural examples

Natural deformation in carbonate mylonites bearing sheet silicates occurs via a complex interaction of granular flow and solution transfer processes and involves continuous cycles of dissolution, grain boundary diffusion, nucleation and growth. In this way, new sheet silicates (a) nucleate within voids formed by grain boundary sliding of calcite grains. (b) grow, and (c) rotate towards the shear plane. As a consequence, small mica grains show a wide range of orientations with respect to the shear plane, but moderate to large grains are subparallel both to each other and to the shear plane. Increases of average grain sizes with increasing temperature of sheet silicates in mica-rich layers is more pronounced than in mica-poor layers. In the calcitic matrix however, sheet silicates can only grow via solution-precipitation and mass transfer processes. Therefore, the observed grain size variability indicates drastic differences in mass transfer behavior between the individual layers, which might be related to differences in the fluid flux. Based on these observations, a conceptual model for the microfabric evolution in sheet silicate bearing mylonites is presented. © 2001 Elsevier Science B.V. All rights reserved.

Granular layer in the periplasmic space of gram-positive bacteria and fine structures of Enterococcus gallinarum and Streptococcus gordonii septa revealed by cryo-electron microscopy of vitreous sections.

High-resolution structural information on optimally preserved bacterial cells can be obtained with cryo-electron microscopy of vitreous sections. With the help of this technique, the existence of a periplasmic space between the plasma membrane and the thick peptidoglycan layer of the gram-positive bacteria Bacillus subtilis and Staphylococcus aureus was recently shown. This raises questions about the mode of polymerization of peptidoglycan. In the present study, we report the structure of the cell envelope of three gram-positive bacteria (B. subtilis, Streptococcus gordonii, and Enterococcus gallinarum). In the three cases, a previously undescribed granular layer adjacent to the plasma membrane is found in the periplasmic space. In order to better understand how nascent peptidoglycan is incorporated into the mature peptidoglycan, we investigated cellular regions known to represent the sites of cell wall production. Each of these sites possesses a specific structure. We propose a hypothetic model of peptidoglycan polymerization that accommodates these differences: peptidoglycan precursors could be exported from the cytoplasm to the periplasmic space, where they could diffuse until they would interact with the interface between the granular layer and the thick peptidoglycan layer. They could then polymerize with mature peptidoglycan. We report cytoplasmic structures at the E. gallinarum septum that could be interpreted as cytoskeletal elements driving cell division (FtsZ ring). Although immunoelectron microscopy and fluorescence microscopy studies have demonstrated the septal and cytoplasmic localization of FtsZ, direct visualization of in situ FtsZ filaments has not been obtained in any electron microscopy study of fixed and dehydrated bacteria.

On the generative equations of fractal self-similarity in granular media and the related PSD models

The physical appearance of granular media suggests the existence of geometrical scale invariance. The paper discuss how this physico-empirical property can be mathematically encoded leading to different generative models: a smooth one encoded by a differential equation and another encoded by an equation coming from a measure theoretical property.

Statistical mechanics approaches to granular media: between micromechanics and macromechanics

The mechanical behavior of granular materials has been traditionally approached through two theoretical and computational frameworks: macromechanics and micromechanics. Macromechanics focuses on continuum based models. In consequence it is assumed that the matter in the granular material is homogeneous and continuously distributed over its volume so that the smallest element cut from the body possesses the same physical properties as the body. In particular, it has some equivalent mechanical properties, represented by complex and non-linear constitutive relationships. Engineering problems are usually solved using computational methods such as FEM or FDM. On the other hand, micromechanics is the analysis of heterogeneous materials on the level of their individual constituents. In granular materials, if the properties of particles are known, a micromechanical approach can lead to a predictive response of the whole heterogeneous material. Two classes of numerical techniques can be differentiated: computational micromechanics, which consists on applying continuum mechanics on each of the phases of a representative volume element and then solving numerically the equations, and atomistic methods (DEM), which consist on applying rigid body dynamics together with interaction potentials to the particles. Statistical mechanics approaches arise between micro and macromechanics. It tries to state which the expected macroscopic properties of a granular system are, by starting from a micromechanical analysis of the features of the particles and the interactions. The main objective of this paper is to introduce this approach.

Representing microstates of static granular matter in a stress phase space

A stress phase space is proposed to compare the static packings of a granular system (microstates) that are compatible to a macrostate described by external stresses. The equivalent stress of each particle of a static packing can be obtained from the mechanical interaction forces, and the associated volume is given by the respective Voronoi cell. Therefore, particles can be located at different stress levels and grouped into categories or configurations, which are defined in base of the geometrical features of the local arrangement (in particular, of the number of forces that keep them force-balanced). They can be represented as points in a stress phase space. The nature of this space is analyzed in detail. The integration limits of the stress variables that avoid or limit tensile states and the capability of each configuration to represent specific stress states establish its main features. Furthermore, if some stress variables are used, instead of the usual components of the Cauchy stress tensor, then some symmetries can be found. Results obtained from molecular dynamics simulations are used to check this nature. Finally, some statistical ensembles are written in terms of the coordinates of this phase space. These require some assumptions that are made in base on continuum mechanics principles.

A packing computational method relating fractal particle size distribution and void fraction in granular media

The study of granular systems is of great interest to many fields of science and technology. The packing of particles affects to the physical properties of the granular system. In particular, the crucial influence of particle size distribution (PSD) on the random packing structure increase the interest in relating both, either theoretically or by computational methods. A packing computational method is developed in order to estimate the void fraction corresponding to a fractal-like particle size distribution.

Thermodynamic aproach to particle size distribution in granular media

The study of particulate systems is of great interest in many fields of science and technology. Soil, sediments, powders, granular materials, colloidal and particulate suspensions are examples of systems involving many size particles. For those systems, the statistical description of the particle size distribution (PSD), that is, the mathematical distribution that defines the relative amounts of particles present, sorted according to size, is a crutial issue. The PSD can be important in understanding soil hydraulic properties, the geological origin or sediments or the physical and chemical properties of granular materials and ceramics, among others.

Computer simulation of random parckings for self-similar particle size distributions in soil and granular materials: porosity and pore size distribution

A 2D computer simulation method of random packings is applied to sets of particles generated by a self-similar uniparametric model for particle size distributions (PSDs) in granular media. The parameter p which controls the model is the proportion of mass of particles corresponding to the left half of the normalized size interval [0,1]. First the influence on the total porosity of the parameter p is analyzed and interpreted. It is shown that such parameter, and the fractal exponent of the associated power scaling, are efficient packing parameters, but this last one is not in the way predicted in a former published work addressing an analogous research in artificial granular materials. The total porosity reaches the minimum value for p = 0.6. Limited information on the pore size distribution is obtained from the packing simulations and by means of morphological analysis methods. Results show that the range of pore sizes increases for decreasing values of p showing also different shape in the volume pore size distribution. Further research including simulations with a greater number of particles and image resolution are required to obtain finer results on the hierarchical structure of pore space.