160 resultados para Particle swarm


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Under lubricated conditions, Al-graphite particle composite is a good antiseizure bearing and antifriction material possessing properties which inhibit excessive temperature rise in bearings. The present study characterizes the dry wear properties of the composite. The dry wear characteristics of the Al-(2.7%–5.7% graphite particle) (50–200μm) composite were found to deteriorate with the addition of graphite, load and sliding distance. Both micro structural and microhardness studies of the worn subsurfaces and analysis of wear debris show that the reductions in strength and ductility of the composite due to graphite addition are the most likely causes of deterioration in the wear properties of the composite.

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A direct method of preparing cast aluminium alloy-graphite particle composites using uncoated graphite particles is reported. The method consists of introducing and dispersing uncoated but suitably pretreated graphite particles in aluminium alloy melts, and casting the resulting composite melts in suitable permanent moulds. The optical pretreatment required for the dispersion of the uncoated graphite particles in aluminium alloy melts consists of heating the graphite particles to 400° C in air for 1 h just prior to their dispersion in the melts. The effects of alloying elements such as Si, Cu and Mg on the dispersability of pretreated graphite in molten aluminium have also been reported. It was found that additions of about 0.5% Mg or 5% Si significantly improve the dispersability of graphite particles in aluminium alloy melts as indicated by the high recoveries of graphite in the castings of these composites. It was also possible to disperse upto 3% graphite in LM 13 alloy melts and retain the graphite particles in a well distributed fashion in the castings using the pre-heat-treated graphite particles. The observations in this study have been related to the information presently available on wetting between graphite and molten aluminium in the presence of different elements and our own thermogravimetric analysis studies on graphite particles. Physical and mechanical properties of LM 13-3% graphite composite made using pre-heat-treated graphite powder, were found to be adequate for many applications, including pistons which have been successfully used in internal combustion engines.

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Considers the magnetic response of a charged Brownian particle undergoing a stochastic birth-death process. The latter simulates the electron-hole pair production and recombination in semiconductors. The authors obtain non-zero, orbital diamagnetism which can be large without violating the Van Leeuwen theorem (1921).

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The damping capacity of cast graphitic aluminum alloy composites has been measured using a torsion pendulum at a constant strain amplitude. It was found that flake-graphite particles dispersed in the matrix of aluminum alloys increased the damping capacity; the improvement was greater, the higher the amount of graphite dispersed in the matrix. At sufficiently high graphite contents the damping capacity of graphitic aluminum composites approaches that of cast iron. The ratio between the damping capacity and the density of graphitic aluminum alloys is higher than cast iron, making them very attractive as light-weight, high-damping materials for possible aircraft applications. Machinability tests on graphite particle-aluminum composites, conducted at speeds of 315 sfm and 525 sfm, showed that the chip length decreased with the amount of graphite of a given size. When the size of graphite was decreased, at a given machining speed, the chip length decreased. Metallographic examination shows that graphite particles act as chip breakers, and are frequently sheared parallel to the plane of the

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The amplification mechanism for the side bands which accompany a large amplitude electron wave on a plasma column are shown to arise due to two mode interaction between negative and positive energy waves.

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Copper- and nickel-coated graphite particles can be successfully introduced into aluminium-base alloy melts as pellets to produce cast aluminium-graphite particle composites. The pellets were made by pressing mixtures of nickel- or copper-coated graphite particles and aluminium powders together at pressures varying between 2 and 20 kg mm–2. These pellets were dispersed in aluminium alloy melts by plunging and holding them in the melts using a refractory coated mild steel cone, until the pellets disintegrated and the powders were dispersed. The optimum pressure for the preparation of pellets was 2 to 5 kg mm–2 and the optimum size and percentage of aluminium powder were 400 to 1000mgrm and 35 wt% respectively. Under optimum conditions the recovery of the graphite particles in the castings was as high as 96%, these particles being pushed into the last freezing interdendritic regions. The tensile strength and the hardness of the graphite aluminium alloys made using the pellet method are comparable to those of similar composites made using gas injection or the vortex method. The pellet method however has the advantage of greater reproducibility and flexibility. Dispersion of graphite particles in the matrix of cast aluminium alloys using the pellet method increases their resistance to wear.

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The effect of a particle size distribution on the fractional reaction has been analysed. The analysis shows that for non-isothermal TG the activation energy and frequency factor evaluated from the fractional reaction by conventional method depend on the particle size distribution, and this may lead to a kinetic compensating effect. Particle size distribution may also lead to an erroneous conclusion about the change in the mechanism of reaction.

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Particle filters find important applications in the problems of state and parameter estimations of dynamical systems of engineering interest. Since a typical filtering algorithm involves Monte Carlo simulations of the process equations, sample variance of the estimator is inversely proportional to the number of particles. The sample variance may be reduced if one uses a Rao-Blackwell marginalization of states and performs analytical computations as much as possible. In this work, we propose a semi-analytical particle filter, requiring no Rao-Blackwell marginalization, for state and parameter estimations of nonlinear dynamical systems with additively Gaussian process/observation noises. Through local linearizations of the nonlinear drift fields in the process/observation equations via explicit Ito-Taylor expansions, the given nonlinear system is transformed into an ensemble of locally linearized systems. Using the most recent observation, conditionally Gaussian posterior density functions of the linearized systems are analytically obtained through the Kalman filter. This information is further exploited within the particle filter algorithm for obtaining samples from the optimal posterior density of the states. The potential of the method in state/parameter estimations is demonstrated through numerical illustrations for a few nonlinear oscillators. The proposed filter is found to yield estimates with reduced sample variance and improved accuracy vis-a-vis results from a form of sequential importance sampling filter.

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Tribology of small inorganic nanoparticles in suspension in a liquid lubricant is often impaired because these particles agglomerate even when organic dispersants are used. In this paper we use lateral force microscopy to study the deformation mechanism and dissipation under traction of two extreme configurations (1) a large MoS2 particle (similar to 20 mu m width) of about 1 mu m height and (2) an agglomerate (similar to 20 mu m width), constituting 50 nm MoS2 crystallites, of about 1 mu m height. The agglomerate records a friction coefficient which is about 5-7 times that of monolithic particle. The paper examines the mechanisms of material removal for both the particles using continuum modeling and microscopy and infers that while the agglomerate response to traction can be accounted for by the bulk mechanical properties of the material, intralayer and interlayer basal planar slips determine the friction and wear of monolithic particles. The results provide a rationale for selection of layered particles, for suspension in liquid lubricants.

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The crucial role of oxide surface chemical composition on ion transport in "soggy sand" electrolytes is discussed in a systematic manner. A prototype soggy sand electrolytic system comprising aerosil silica functionalized with various hydrophilic and hydrophobic moieties dispersed in lithium perchlorate-ethylene glycol solution was used for the study. Detailed rheology studies show that the attractive particle network in the case of the composite with unmodified aerosil silica (with surface silanol groups) is most favorable for percolation in ionic conductivity, as well as rendering the composite with beneficial elastic mechanical properties: Though weaker in strength compared to the composite with unmodified aerosil particles, attractive particle networks are also observed in composites of aerosil particles with surfaces partially substituted with hydrophobic groups. The percolation in ionic conductivity is, however, dependent on the size of the hydrophobic moiety. No spanning attractive particle network was formed for aerosil particles with surfaces modified with stronger hydrophilic groups (than silanol), and as a result, no percolation in ionic conductivity was observed. The composite with hydrophilic particles was a sol, contrary to gels obtained in the case of unmodified aerosil, and partially substituted with hydrophobic groups.

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The problem of identifying parameters of nonlinear vibrating systems using spatially incomplete, noisy, time-domain measurements is considered. The problem is formulated within the framework of dynamic state estimation formalisms that employ particle filters. The parameters of the system, which are to be identified, are treated as a set of random variables with finite number of discrete states. The study develops a procedure that combines a bank of self-learning particle filters with a global iteration strategy to estimate the probability distribution of the system parameters to be identified. Individual particle filters are based on the sequential importance sampling filter algorithm that is readily available in the existing literature. The paper develops the requisite recursive formulary for evaluating the evolution of weights associated with system parameter states. The correctness of the formulations developed is demonstrated first by applying the proposed procedure to a few linear vibrating systems for which an alternative solution using adaptive Kalman filter method is possible. Subsequently, illustrative examples on three nonlinear vibrating systems, using synthetic vibration data, are presented to reveal the correct functioning of the method. (c) 2007 Elsevier Ltd. All rights reserved.

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The role of oxide surface chemical composition and solvent on ion solvation and ion transport of ``soggy sand'' electrolytes are discussed here. A ``soggy sand'' electrolyte system comprising dispersions of hydrophilic/hydrophobic functionalized aerosil silica in lithium perchlorate methoxy polyethylene glycol solution was employed for the study. Static and dynamic rheology measurements show formation of an attractive particle network in the case of the composite with unmodified aerosil silica (i.e., with surface silanol groups) as well as composites with hydrophobic alkane groups. While particle network in the composite with hydrophilic aerosil silica (unmodified) were due to hydrogen bonding, hydrophobic aerosil silica particles were held together via van der Waals forces. The network strength in the latter case (i.e., for hydrophobic composites) were weaker compared with the composite with unmodified aerosil silica. Both unmodified silica as well as hydrophobic silica composites displayed solid-like mechanical strength. No enhancement in ionic conductivity compared to the liquid electrolyte was observed in the case of the unmodified silica. This was attributed to the existence of a very strong particle network, which led to the ``expulsion'' of all conducting entities from the interfacial region between adjacent particles. The ionic conductivity for composites with hydrophobic aerosil particles displayed ionic conductivity dependent on the size of the hydrophobic chemical moiety. No spanning attractive particle network was observed for aerosil particles with surfaces modified with stronger hydrophilic groups (than silanol). The composite resembled a sol, and no percolation in ionic conductivity was observed.

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The problem of identification of parameters of a beam-moving oscillator system based on measurement of time histories of beam strains and displacements is considered. The governing equations of motion here have time varying coefficients. The parameters to be identified are however time invariant and consist of mass, stiffness and damping characteristics of the beam and oscillator subsystems. A strategy based on dynamic state estimation method, that employs particle filtering algorithms, is proposed to tackle the identification problem. The method can take into account measurement noise, guideway unevenness, spatially incomplete measurements, finite element models for supporting structure and moving vehicle, and imperfections in the formulation of the mathematical models. Numerical illustrations based on synthetic data on beam-oscillator system are presented to demonstrate the satisfactory performance of the proposed procedure.

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This paper presents a glowworm metaphor based distributed algorithm that enables a collection of minimalist mobile robots to split into subgroups, exhibit simultaneous taxis-behavior towards, and rendezvous at multiple radiation sources such as nuclear/hazardous chemical spills and fire-origins in a fire calamity. The algorithm is based on a glowworm swarm optimization (GSO) technique that finds multiple optima of multimodal functions. The algorithm is in the same spirit as the ant-colony optimization (ACO) algorithms, but with several significant differences. The agents in the glowworm algorithm carry a luminescence quantity called luciferin along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luciferin. The key feature that is responsible for the working of the algorithm is the use of an adaptive local-decision domain, which we use effectively to detect the multiple source locations of interest. The glowworms have a finite sensor range which defines a hard limit on the local-decision domain used to compute their movements. Extensive simulations validate the feasibility of applying the glowworm algorithm to the problem of multiple source localization. We build four wheeled robots called glowworms to conduct our experiments. We use a preliminary experiment to demonstrate the basic behavioral primitives that enable each glowworm to exhibit taxis behavior towards source locations and later demonstrate a sound localization task using a set of four glowworms.

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Perfectly hard particles are those which experience an infinite repulsive force when they overlap, and no force when they do not overlap. In the hard-particle model, the only static state is the isostatic state where the forces between particles are statically determinate. In the flowing state, the interactions between particles are instantaneous because the time of contact approaches zero in the limit of infinite particle stiffness. Here, we discuss the development of a hard particle model for a realistic granular flow down an inclined plane, and examine its utility for predicting the salient features both qualitatively and quantitatively. We first discuss Discrete Element simulations, that even very dense flows of sand or glass beads with volume fraction between 0.5 and 0.58 are in the rapid flow regime, due to the very high particle stiffness. An important length scale in the shear flow of inelastic particles is the `conduction length' delta = (d/(1 - e(2))(1/2)), where d is the particle diameter and e is the coefficient of restitution. When the macroscopic scale h (height of the flowing layer) is larger than the conduction length, the rates of shear production and inelastic dissipation are nearly equal in the bulk of the flow, while the rate of conduction of energy is O((delta/h)(2)) smaller than the rate of dissipation of energy. Energy conduction is important in boundary layers of thickness delta at the top and bottom. The flow in the boundary layer at the top and bottom is examined using asymptotic analysis. We derive an exact relationship showing that the a boundary layer solution exists only if the volume fraction in the bulk decreases as the angle of inclination is increased. In the opposite case, where the volume fraction increases as the angle of inclination is increased, there is no boundary layer solution. The boundary layer theory also provides us with a way of understanding the cessation of flow when at a given angle of inclination when the height of the layer is decreased below a value h(stop), which is a function of the angle of inclination. There is dissipation of energy due to particle collisions in the flow as well as due to particle collisions with the base, and the fraction of energy dissipation in the base increases as the thickness decreases. When the shear production in the flow cannot compensate for the additional energy drawn out of the flow due to the wall collisions, the temperature decreases to zero and the flow stops. Scaling relations can be derived for h(stop) as a function of angle of inclination.