827 resultados para Multiple-scale processing


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In this paper the renormalization group (RG) method of Chen, Goldenfeld, and Oono [Phys. Rev. Lett., 73 (1994), pp.1311-1315; Phys. Rev. E, 54 (1996), pp.376-394] is presented in a pedagogical way to increase its visibility in applied mathematics and to argue favorably for its incorporation into the corresponding graduate curriculum.The method is illustrated by some linear and nonlinear singular perturbation problems. Key word. © 2012 Society for Industrial and Applied Mathematics.

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Following the derivation of amplitude equations through a new two-time-scale method [O'Malley, R. E., Jr. & Kirkinis, E (2010) A combined renormalization group-multiple scale method for singularly perturbed problems. Stud. Appl. Math. 124, 383-410], we show that a multi-scale method may often be preferable for solving singularly perturbed problems than the method of matched asymptotic expansions. We illustrate this approach with 10 singularly perturbed ordinary and partial differential equations. © 2011 Cambridge University Press.

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Microalgae dewatering is a major obstruction to industrial-scale processing of microalgae for biofuel prodn. The dil. nature of harvested microalgal cultures creates a huge operational cost during dewatering, thereby, rendering algae-based fuels less economically attractive. Currently there is no superior method of dewatering microalgae. A technique that may result in a greater algal biomass may have drawbacks such as a high capital cost or high energy consumption. The choice of which harvesting technique to apply will depend on the species of microalgae and the final product desired. Algal properties such as a large cell size and the capability of the microalgae to autoflocculate can simplify the dewatering process. This article reviews and addresses the various technologies currently used for dewatering microalgal cultures along with a comparative study of the performances of the different technologies.

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Dewatering of microalgal culture is a major bottleneck towards the industrial-scale processing of microalgae for bio-diesel production. The dilute nature of harvested microalgal cultures poses a huge operation cost to dewater; thereby rendering microalgae-based fuels less economically attractive. This study explores the influence of microalgal growth phases and intercellular interactions during cultivation on dewatering efficiency of microalgae cultures. Experimental results show that microalgal cultures harvested during a low growth rate phase (LGRP) of 0.03 d-1 allowed a higher rate of settling than those harvested during a high growth rate phase (HGRP) of 0.11 d-1, even though the latter displayed a higher average differential biomass concentration of 0.2 g L-1 d-1. Zeta potential profile during the cultivation process showed a maximum electronegative value of -43.2 ± 0.7 mV during the HGRP which declined to stabilization at -34.5 ± 0.4 mV in the LGRP. The lower settling rate observed for HGRP microalgae is hence attributed to the high stability of the microalgal cells which electrostatically repel each other during this growth phase. Tangential flow filtration of 20 L HGRP culture concentrated 23 times by consuming 0.51 kWh/m3 of supernatant removed whilst 0.38 kWh/m3 was consumed to concentrate 20 L of LGRP by 48 times.

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In the cylindrical coordinate system, a singular perturbation theory of multiple-scale asymptotic expansions was developed to study single standing water wave mode by solving potential equations of water waves in a rigid circular cylinder, which is subjec

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A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surface filling-in occurs; how surface filling-in interacts with spatial attention to generate a form-fitting distribution of spatial attention, or attentional shroud; how the strongest shroud can inhibit weaker shrouds; and how the winning shroud regulates learning of texture categories, and thus the allocation of object attention. The model can discriminate abutted textures with blurred boundaries and is sensitive to texture boundary attributes like discontinuities in orientation and texture flow curvature as well as to relative orientations of texture elements. The model quantitatively fits a large set of human psychophysical data on orientation-based textures. Object boundar output of the model is compared to computer vision algorithms using a set of human segmented photographic images. The model classifies textures and suppresses noise using a multiple scale oriented filterbank and a distributed Adaptive Resonance Theory (dART) classifier. The matched signal between the bottom-up texture inputs and top-down learned texture categories is utilized by oriented competitive and cooperative grouping processes to generate texture boundaries that control surface filling-in and spatial attention. Topdown modulatory attentional feedback from boundary and surface representations to early filtering stages results in enhanced texture boundaries and more efficient learning of texture within attended surface regions. Surface-based attention also provides a self-supervising training signal for learning new textures. Importance of the surface-based attentional feedback in texture learning and classification is tested using a set of textured images from the Brodatz micro-texture album. Benchmark studies vary from 95.1% to 98.6% with attention, and from 90.6% to 93.2% without attention.

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Not all introduced (invasive) species in a region will spread from a single point of introduction. Long-distance dispersal or further introductions can obscure the pattern of spread, but the regional importance of such processes is difficult to gauge. These difficulties are further compounded when information on the multiple scale process of invasive species range expansion is reduced to one-dimensional estimates of spread (e. g. km yr(-1)). We therefore compared the results of two different metrics of range expansion: maximum linear rate of spread and accumulation of occupied grid squares (50 x 50 km) over time. An analysis of records for 54 species of introduced marine macrophytes in the Mediterranean and northeast Atlantic revealed cases where the invasion process was probably missed (e. g. Atlantic Bonnemaisonia hamifera) and suggested cases of secondary introductions or erratic jump dispersal (Dasysiphonia sp. and Womersleyella setacea). A majority of species analysed showed evidence for an accumulation of invaded sites without a clear invasion front. Estimates of spread rate are increasing for more recent introductions. The increase is greater than can be accounted for by temporally varying search effort and implies a historical increase in vector efficiency and/or a decreased resistance of native communities to invasion.

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A theoretical study is presented of the nonlinear amplitude modulation of waves propagating in unmagnetized plasmas contaminated by charged dust particles. Distinct well-known dusty plasma modes are explicitly considered, namely, the dust-acoustic wave, the dust-ion acoustic wave, and transverse dust-lattice waves. Using a multiple-scale technique, a nonlinear Schrodinger-type equation is derived, describing the evolution of the wave amplitude. A stability analysis reveals the possibility for modulational instability to occur, possibly leading to the formation of different types of envelope-localized excitations (solitary waves), under conditions which depend on the wave dispersion laws and intrinsic dusty plasma parameters.

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The Nonlinear self-modulation of dust acoustic waves is studied in the presence of non-thermal (non-Maxwellian) ion and electron populations. By employing a multiple scale technique, a nonlinear Schrodinger-type equation (NLSE) is derived for the wave amplitude. The influence of non-thermality, in addition to obliqueness (between the propagation and modulation directions), on the conditions for modulational instability to occur is discussed. Different types of localized solutions (envelope excitations) which may possibly occur are discussed, and the dependence of their characteristics oil physical parameters is traced. The ion deviation from a Maxwellian distribution comes out to be more important than the electron analogous deviation alone. Both yield a de-stabilizing effect oil (the amplitude of) DAWs propagating in a dusty plasma with negative dust grains, and thus favour the formation of bright- (rather than dark-) type envelope structures, (solitons) in the plasma. A similar tendency towards amplitude de-stabilization is found for the ease of the presence of positively charged dust in the plasma.

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Abundant evidence for the occurrence of modulated envelope plasma wave packets is provided by recent satellite missions. These excitations are characterized by a slowly varying localized envelope structure, embedding the fast carrier wave, which appears to be the result of strong modulation of the wave amplitude. This modulation may be due to parametric interactions between different modes or, simply, to the nonlinear (self-)interaction of the carrier wave. A generic exact theory is presented in this study, for the nonlinear self-modulation of known electrostatic plasma modes, by employing a collisionless fluid model. Both cold (zero-temperature) and warm fluid descriptions are discussed and the results are compared. The (moderately) nonlinear oscillation regime is investigated by applying a multiple scale technique. The calculation leads to a Nonlinear Schrodinger-type Equation (NLSE), which describes the evolution of the slowly varying wave amplitude in time and space. The NLSE admits localized envelope (solitary wave) solutions of bright(pulses) or dark- (holes, voids) type, whose characteristics (maximum amplitude, width) depend on intrinsic plasma parameters. Effects like amplitude perturbation obliqueness (with respect to the propagation direction), finite temperature and defect (dust) concentration are explicitly considered. Relevance with similar highly localized modulated wave structures observed during recent satellite missions is discussed.

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A pair plasma consisting of two types of ions, possessing equal masses and opposite charges, is considered. The nonlinear propagation of modulated electrostatic wave packets is studied by employing a two-fluid plasma model. Considering propagation parallel to the external magnetic field, two distinct electrostatic modes are obtained, namely a quasiacoustic lower moddfe and a Langmuir-like, as optic-type upper one, in agreement with experimental observations and theoretical predictions. Considering small yet weakly nonlinear deviations from equilibrium, and adopting a multiple-scale technique, the basic set of model equations is reduced to a nonlinear Schrodinger equation for the slowly varying electric field perturbation amplitude. The analysis reveals that the lower (acoustic) mode is stable and may propagate in the form of a dark-type envelope soliton (a void) modulating a carrier wave packet, while the upper linear mode is intrinsically unstable, and may favor the formation of bright-type envelope soliton (pulse) modulated wave packets. These results are relevant to recent observations of electrostatic waves in pair-ion (fullerene) plasmas, and also with respect to electron-positron plasma emission in pulsar magnetospheres. (c) 2006 American Institute of Physics.

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A conceptual model is described for generating distributions of grazing animals, according to their searching behavior, to investigate the mechanisms animals may use to achieve their distributions. The model simulates behaviors ranging from random diffusion, through taxis and cognitively aided navigation (i.e., using memory), to the optimization extreme of the Ideal Free Distribution. These behaviors are generated from simulation of biased diffusion that operates at multiple scales simultaneously, formalizing ideas of multiple-scale foraging behavior. It uses probabilistic bias to represent decisions, allowing multiple search goals to be combined (e.g., foraging and social goals) and the representation of suboptimal behavior. By allowing bias to arise at multiple scales within the environment, each weighted relative to the others, the model can represent different scales of simultaneous decision-making and scale-dependent behavior. The model also allows different constraints to be applied to the animal's ability (e.g., applying food-patch accessibility and information limits). Simulations show that foraging-decision randomness and spatial scale of decision bias have potentially profound effects on both animal intake rate and the distribution of resources in the environment. Spatial variograms show that foraging strategies can differentially change the spatial pattern of resource abundance in the environment to one characteristic of the foraging strategy.</

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A brief review of the occurrence of amplitude modulated structures in space and laboratory plasmas is provided, followed by a theoretical analysis of the mechanism of carrier wave (self-) interaction, with respect to electrostatic plasma modes. A generic collisionless unmagnetized fluid model is employed. Both cold-(zero-temperature) and warm-(finite temperature) fluid descriptions are considered and compared. The weakly nonlinear oscillation regime is investigated by applying a multiple scale (reductive perturbation) technique and a Nonlinear Schrödinger Equation (NLSE) is obtained, describing the evolution of the slowly varying wave amplitude in time and space. The amplitude’s stability profile reveals the possibility of modulational instability to occur under the influence of external perturbations. The NLSE admits exact localized envelope (solitary wave) solutions of bright (pulses) or dark (holes, voids) type, whose characteristics depend on intrinsic plasma parameters. The role of perturbation obliqueness (with respect to the propagation direction), finite temperature and — possibly — defect (dust) concentration is explicitly considered. The relevance of this description with respect to known electron-ion (e-i) as well as dusty (complex) plasma modes is briefly discussed. © 2004 American Institute of Physics

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The combination of milli-scale processing and microwave heating has been investigated for the Cu-catalyzed Ullmann etherification in fine-chemical synthesis, providing improved catalytic activity and selective catalyst heating. Wall-coated and fixed-bed milli-reactors were designed and applied in the Cu-catalyzed Ullmann-type CO coupling of phenol and 4-chloropyridine. In a batch reactor the results show clearly increased yields for the microwave heated process at low microwave powers, whereas high powers and catalyst loadings reduced the benefits of microwave heating. Slightly higher yields were found in the Cu/ZnO wall-coated as compared to the Cu/TiO fixed-bed flow-reactor. The benefit here is that the reaction occurs at the surface of the metal nanoparticles confined within a support film making the nano-copper equally accessible. Catalyst deactivation was mainly caused by Cu oxidation and coke formation; however, at longer process times leaching played a significant role. Catalyst activity could partially be recovered by removal of deposited by-product by means of calcination. After 6h on-stream the reactor productivities were 28.3 and 55.1kgprod/(mR3h) for the fresh Cu/ZnO wall-coated and Cu/TiO fixed-bed reactor, respectively. Comparison of single- and multimode microwaves showed a threefold yield increase for single-mode microwaves. Control of nanoparticles size and loading allows to avoid high temperatures in a single-mode microwave field and provides a novel solution to a major problem for combining metal catalysis and microwave heating. Catalyst stability appeared to be more important and provided twofold yield increase for the CuZn/TiO catalyst as compared to the Cu/TiO catalyst due to stabilized copper by preferential oxidation of the zinc. For this catalyst a threefold yield increase was observed in single-mode microwaves which, to the best of our knowledge, led to a not yet reported productivity of 172kgprod/(mR3h) for the microwave and flow Ullmann CO coupling. © 2012 Elsevier B.V.

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Community structure depends on both deterministic and stochastic processes. However, patterns of community dissimilarity (e.g. difference in species composition) are difficult to interpret in terms of the relative roles of these processes. Local communities can be more dissimilar (divergence) than, less dissimilar (convergence) than, or as dissimilar as a hypothetical control based on either null or neutral models. However, several mechanisms may result in the same pattern, or act concurrently to generate a pattern, and much research has recently been focusing on unravelling these mechanisms and their relative contributions. Using a simulation approach, we addressed the effect of a complex but realistic spatial structure in the distribution of the niche axis and we analysed patterns of species co-occurrence and beta diversity as measured by dissimilarity indices (e.g. Jaccard index) using either expectations under a null model or neutral dynamics (i.e., based on switching off the niche effect). The strength of niche processes, dispersal, and environmental noise strongly interacted so that niche-driven dynamics may result in local communities that either diverge or converge depending on the combination of these factors. Thus, a fundamental result is that, in real systems, interacting processes of community assembly can be disentangled only by measuring traits such as niche breadth and dispersal. The ability to detect the signal of the niche was also dependent on the spatial resolution of the sampling strategy, which must account for the multiple scale spatial patterns in the niche axis. Notably, some of the patterns we observed correspond to patterns of community dissimilarities previously observed in the field and suggest mechanistic explanations for them or the data required to solve them. Our framework offers a synthesis of the patterns of community dissimilarity produced by the interaction of deterministic and stochastic determinants of community assembly in a spatially explicit and complex context.