471 resultados para Percolation


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Percolation flow problems are discussed in many research fields, such as seepage hydraulics, groundwater hydraulics, groundwater dynamics and fluid dynamics in porous media. Many physical processes appear to exhibit fractional-order behavior that may vary with time, or space, or space and time. The theory of pseudodifferential operators and equations has been used to deal with this situation. In this paper we use a fractional Darcys law with variable order Riemann-Liouville fractional derivatives, this leads to a new variable-order fractional percolation equation. In this paper, a new two-dimensional variable-order fractional percolation equation is considered. A new implicit numerical method and an alternating direct method for the two-dimensional variable-order fractional model is proposed. Consistency, stability and convergence of the implicit finite difference method are established. Finally, some numerical examples are given. The numerical results demonstrate the effectiveness of the methods. This technique can be used to simulate a three-dimensional variable-order fractional percolation equation.

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X-ray microtomography (micro-CT) with micron resolution enables new ways of characterizing microstructures and opens pathways for forward calculations of multiscale rock properties. A quantitative characterization of the microstructure is the first step in this challenge. We developed a new approach to extract scale-dependent characteristics of porosity, percolation, and anisotropic permeability from 3-D microstructural models of rocks. The Hoshen-Kopelman algorithm of percolation theory is employed for a standard percolation analysis. The anisotropy of permeability is calculated by means of the star volume distribution approach. The local porosity distribution and local percolation probability are obtained by using the local porosity theory. Additionally, the local anisotropy distribution is defined and analyzed through two empirical probability density functions, the isotropy index and the elongation index. For such a high-resolution data set, the typical data sizes of the CT images are on the order of gigabytes to tens of gigabytes; thus an extremely large number of calculations are required. To resolve this large memory problem parallelization in OpenMP was used to optimally harness the shared memory infrastructure on cache coherent Non-Uniform Memory Access architecture machines such as the iVEC SGI Altix 3700Bx2 Supercomputer. We see adequate visualization of the results as an important element in this first pioneering study.

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It is shown that for continuum percolation with overlapping discs having a distribution of radii, the net areal density of discs at percolation threshold depends non-trivially on the distribution, and is not bounded by any finite constant. Results of a Monte Carlo simulation supporting the argument are presented.

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Underlying the unique structures and diverse functions of proteins area vast range of amino-acid sequences and a highly limited number of folds taken up by the polypeptide backbone. By investigating the role of noncovalent connections at the backbone level and at the detailed side-chain level, we show that these unique structures emerge from interplay between random and selected features. Primarily, the protein structure network formed by these connections shows simple (bond) and higher order (clique) percolation behavior distinctly reminiscent of random network models. However, the clique percolation specific to the side-chain interaction network bears signatures unique to proteins characterized by a larger degree of connectivity than in random networks. These studies reflect some salient features of the manner in which amino acid sequences select the unique structure of proteins from the pool of a limited number of available folds.

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Composites of Polystyrene-multi wall carbon nanotubes (PS-MWNTs) were prepared with loading up to 7 wt% of MWNTs by simple solvent mixing and drying technique. MWNTs with high aspect ratio similar to 4000 were used to make the polymer composites. A very high degree of dispersion of MWNTs was achieved by ultrasonication technique. As a result of high dispersion and high aspect ratio of the MWNTs electrical percolation was observed at rather low weight fraction similar to 0.0021. Characterization of the as prepared PS-MWNTs composites was done by Electron microscopy (EM), X-ray diffraction technique (XRD) and Thermogravimetery analysis (TGA).

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In multiwall carbon nanotube (MWNT)-polystyrene (PS) composites, a weak temperature dependence of conductivity has been observed at a percolation threshold of 0.4 wt %. The power law [sigma(T)proportional to T-0.3] behavior indicates metallic-like behavior, unlike the usual activated transport for systems near the percolation threshold. The low field positive magnetoconductance follows H-2 dependence, due to the weak localization in disordered metallic systems. The marginal metallic nature of MWNT-PS at percolation threshold is further verified from the negligible frequency dependence of conductivity, in the temperature range of 300 to 5 K. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3455895]

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Randomly diluted quantum boson and spin models in two dimensions combine the physics of classical percolation with the well-known dimensionality dependence of ordering in quantum lattice models. This combination is rather subtle for models that order in two dimensions but have no true order in one dimension, as the percolation cluster near threshold is a fractal of dimension between 1 and 2: two experimentally relevant examples are the O(2) quantum rotor and the Heisenberg antiferromagnet. We study two analytic descriptions of the O(2) quantum rotor near the percolation threshold. First a spin-wave expansion is shown to predict long-ranged order, but there are statistically rare points on the cluster that violate the standard assumptions of spin-wave theory. A real-space renormalization group (RSRG) approach is then used to understand how these rare points modify ordering of the O(2) rotor. A new class of fixed points of the RSRG equations for disordered one-dimensional bosons is identified and shown to support the existence of long-range order on the percolation backbone in two dimensions. These results are relevant to experiments on bosons in optical lattices and superconducting arrays, and also (qualitatively) for the diluted Heisenberg antiferromagnet La-2(Zn,Mg)(x)Cu1-xO4.

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Polystyrene/multiwall carbon nanotube composite films are prepared with loading up to 7 weight percent (wt%) of multiwall carbon nanotubes by solution processing and casting technique. In the formation of these composite films, iron filled carbon nanotubes with high aspect ratio (similar to 4000) were used. Scanning electron microscopy study shows that the nanotubes are uniformly dispersed within the polymer matrix. At high magnification, bending of carbon nanotubes is noticed which can be attributed to their elastic properties. The electrical conductivity measurements show that the percolation threshold is rather low at 0.21 wt%. Hysteresis loop measurements on the bulk multiwall carbon nanotube and composite samples are done at 10, 150 and 300 K and the coercivity values are found to be largest at all the temperatures, for 1 wt% composite sample. (C) 2010 Elsevier B.V. All rights reserved.

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Given two independent Poisson point processes ©(1);©(2) in Rd, the AB Poisson Boolean model is the graph with points of ©(1) as vertices and with edges between any pair of points for which the intersection of balls of radius 2r centred at these points contains at least one point of ©(2). This is a generalization of the AB percolation model on discrete lattices. We show the existence of percolation for all d ¸ 2 and derive bounds for a critical intensity. We also provide a characterization for this critical intensity when d = 2. To study the connectivity problem, we consider independent Poisson point processes of intensities n and cn in the unit cube. The AB random geometric graph is de¯ned as above but with balls of radius r. We derive a weak law result for the largest nearest neighbour distance and almost sure asymptotic bounds for the connectivity threshold.

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Temperature modulated alternating differential scanning calorimetric studies show that Se rich Ge0.15Se0.85−xAgx (0 x 0.20) glasses are microscopically phase separated, containing Ag2Se phases embedded in a Ge0.15Se0.85 backbone. With increasing silver concentration, Ag2Se phase percolates in the Ge–Se matrix, with a well-defined percolation threshold at x = 0.10. A signature of this percolation transition is shown up in the thermal behavior, as the appearance of two exothermic crystallization peaks. Density, molar volume, and microhardness measurements, undertaken in the present study, also strongly support this view of percolation transition. The superionic conduction observed earlier in these glasses at higher silver proportions is likely to be connected with the silver phase percolation.

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Given two independent Poisson point processes Phi((1)), Phi((2)) in R-d, the AB Poisson Boolean model is the graph with the points of Phi((1)) as vertices and with edges between any pair of points for which the intersection of balls of radius 2r centered at these points contains at least one point of Phi((2)). This is a generalization of the AB percolation model on discrete lattices. We show the existence of percolation for all d >= 2 and derive bounds fora critical intensity. We also provide a characterization for this critical intensity when d = 2. To study the connectivity problem, we consider independent Poisson point processes of intensities n and tau n in the unit cube. The AB random geometric graph is defined as above but with balls of radius r. We derive a weak law result for the largest nearest-neighbor distance and almost-sure asymptotic bounds for the connectivity threshold.

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Drawing inspiration from real world interacting systems, we study a system consisting of two networks that exhibit antagonistic and dependent interactions. By antagonistic and dependent interactions we mean that a proportion of functional nodes in a network cause failure of nodes in the other, while failure of nodes in the other results in failure of links in the first. In contrast to interdependent networks, which can exhibit first-order phase transitions, we find that the phase transitions in such networks are continuous. Our analysis shows that, compared to an isolated network, the system is more robust against random attacks. Surprisingly, we observe a region in the parameter space where the giant connected components of both networks start oscillating. Furthermore, we find that for Erdos-Renyi and scale-free networks the system oscillates only when the dependence and antagonism between the two networks are very high. We believe that this study can further our understanding of real world interacting systems.