955 resultados para Molar - Average distances


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This paper presents a comparative evaluation of the average and switching models of a dc-dc boost converter from the point of view of real-time simulation. Both the models are used to simulate the converter in real-time on a Field Programmable Gate Array (FPGA) platform. The converter is considered to function over a wide range of operating conditions, and could do transition between continuous conduction mode (CCM) and discontinuous conduction mode (DCM). While the average model is known to be computationally efficient from the perspective of off-line simulation, the same is shown here to consume more logical resources than the switching model for real-time simulation of the dc-dc converter. Further, evaluation of the boundary condition between CCM and DCM is found to be the main reason for the increased consumption of resources by the average model.

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Na0.5Bi0.5TiO3 (NBT) and its derivatives have prompted a great surge in interest owing to their potential as lead-free piezoelectrics. In spite of five decades since its discovery, there is still a lack of clarity on crucial issues such as the origin of significant dielectric relaxation at room temperature, structural factors influencing its depoling, and the status of the recently proposed monoclinic (Cc) structure vis-a-vis the nanosized structural heterogeneities. In this work, these issues are resolved by comparative analysis of local and global structures on poled and unpoled NBT specimens using electron, x-ray, and neutron diffraction in conjunction with first-principles calculation, dielectric, ferroelectric, and piezoelectric measurements. The reported global monoclinic (Cc) distortion is shown not to correspond to the thermodynamic equilibrium state at room temperature. The global monocliniclike appearance rather owes its origin to the presence of local structural and strain heterogeneities. Poling removes the structural inhomogeneities and establishes a long-range rhombohedral distortion. In the process the system gets irreversibly transformed from a nonergodic relaxor to a normal ferroelectric state. The thermal depoling is shown to be associated with the onset of incompatible in-phase tilted octahedral regions in the field-stabilized long range rhombohedral distortion.

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We consider a discrete time partially observable zero-sum stochastic game with average payoff criterion. We study the game using an equivalent completely observable game. We show that the game has a value and also we present a pair of optimal strategies for both the players.

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Voltage source inverters are an integral part of renewable power sources and smart grid systems. Computationally efficient and fairly accurate models for the voltage source inverter are required to carry out extensive simulation studies on complex power networks. Accuracy requires that the effect of dead-time be incorporated in the inverter model. The dead-time is essentially a short delay introduced between the gating pulses to the complementary switches in an inverter leg for the safety of power devices. As the modern voltage source inverters switch at fairly high frequencies, the dead-time significantly influences the output fundamental voltage. Dead-time also causes low-frequency harmonic distortion and is hence important from a power quality perspective. This paper studies the dead-time effect in a synchronous dq reference frame, since dynamic studies and controller design are typically carried out in this frame of reference. For the sake of computational efficiency, average models are derived, incorporating the dead-time effect, in both RYB and dq reference frames. The average models are shown to consume less computation time than their corresponding switching models, the accuracies of the models being comparable. The proposed average synchronous reference frame model, including effect of dead-time, is validated through experimental results.

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A controllable synthesis of phase pure wurtzite (WZ) ZnS nanostructures has been reported in this work at a low temperature of similar to 220 degrees C using ethylenediamine as the soft template and by varying the molar concentration of zinc to sulphur precursors as well as by using different precursors. A significant reduction in the formation temperature required for the synthesis of phase pure WZ ZnS has been observed. A strong correlation has been observed between the morphology of the synthesized ZnS nanostructures and the precursors used during synthesis. It has been found from Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM) image analyses that the morphology of the ZnS nanocrystals changes from a block-like to a belt-like structure having an average length of similar to 450 nm when the molar ratio of zinc to sulphur source is increased from 1 : 1 to 1 : 3. An oriented attachment (OA) growth mechanism has been used to explain the observed shape evolution of the synthesized nanostructures. The synthesized nanostructures have been characterized by the X-ray diffraction technique as well as by UV-Vis absorption and photoluminescence (PL) emission spectroscopy. The as-synthesized nanobelts exhibit defect related visible PL emission. On isochronal annealing of the nanobelts in air in the temperature range of 100-600 degrees C, it has been found that white light emission with a Commission Internationale de I'Eclairage 1931 (CIE) chromaticity coordinate of (0.30, 0.34), close to that of white light (0.33, 0.33), can be obtained from the ZnO nanostructures obtained at an annealing temperature of 600 degrees C. UV light driven degradation of methylene blue (MB) dye aqueous solution has also been demonstrated using as-synthesized nanobelts and similar to 98% dye degradation has been observed within only 40 min of light irradiation. The synthesized nanobelts with visible light emission and having dye degradation activity can be used effectively in future optoelectronic devices and in water purification for cleaning of dyes.

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Extensive molecular dynamics studies of 13 different silica polymorphs are reported in the isothermal-isobaric ensemble with the Parrinello-Rahman variable shape simulation cell. The van Beest-Kramer-van Santen (BKS) potential is shown to predict lattice parameters for most phases within 2%-3% accuracy, as well as the relative stabilities of different polymorphs in agreement with experiment. Enthalpies of high-density polymorphs - CaCl2-type, alpha-PbO2-type, and pyrite-type for which no experimental data are available as yet, are predicted here. Further, the calculated enthalpies exhibit two distinct regimes as a function of molar volume-for low and medium-density polymorphs, it is almost independent of volume, while for high-pressure phases a steep dependence is seen. A detailed analysis indicates that the increased short-range contributions to enthalpy in the high-density phases arise not only from an increased coordination number of silicon but also shorter Si-O bond lengths. Our results indicate that amorphous phases of silica exhibit better optimization of short-range interactions than crystalline phases at the same density while the magnitude of Coulombic contributions is lower in the amorphous phase. (C) 2014 AIP Publishing LLC.

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Cobalt ferrite nanoparticles with average sizes of 14, 9 and 6 nm were synthesised by the chemical co-precipitation technique. Average particle sizes were varied by changing the chitosan surfactant to precursor molar ratio in the reaction mixture. Transmission electron microscopy images revealed a faceted and irregular morphology for the as-synthesised nanoparticles. Magnetic measurements revealed a ferromagnetic nature for the 14 and 9 nm particles and a superparamagnetic nature for the 6 nm particles. An increase in saturation magnetisation with increasing particle size was noted. Relaxivity measurements were carried out to determine T-2 value as a function of particle size using nuclear magnetic resonance measurements. The relaxivity coefficient increased with decrease in particle size and decrease in the saturation magnetisation value. The observed trend in the change of relaxivity value with particle size was attributed to the faceted nature of as-synthesised nanoparticles. Faceted morphology results in the creation of high gradient of magnetic field in the regions adjacent to the facet edges increasing the relaxivity value. The effect of edges in increasing the relaxivity value increases with decrease in the particle size because of an increase in the total number of edges per particle dispersion.

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The role of the molar volume on the estimated diffusion parameters has been speculated for decades. The Matano-Boltzmann method was the first to be developed for the estimation of the variation of the interdiffusion coefficients with composition. However, this could be used only when the molar volume varies ideally or remains constant. Although there are no such systems, this method is still being used to consider the ideal variation. More efficient methods were developed by Sauer-Freise, Den Broeder, and Wagner to tackle this problem. However, there is a lack of research indicating the most efficient method. We have shown that Wagner's method is the most suitable one when the molar volume deviates from the ideal value. Similarly, there are two methods for the estimation of the ratio of intrinsic diffusion coefficients at the Kirkendall marker plane proposed by Heumann and van Loo. The Heumann method, like the Matano-Boltzmann method, is suitable to use only when the molar volume varies more or less ideally or remains constant. In most of the real systems, where molar volume deviates from the ideality, it is safe to use the van Loo method. We have shown that the Heumann method introduces large errors even for a very small deviation of the molar volume from the ideal value. On the other hand, the van Loo method is relatively less sensitive to it. Overall, the estimation of the intrinsic diffusion coefficient is more sensitive than the interdiffusion coefficient.

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Cooperative relaying combined with selection exploits spatial diversity to significantly improve the performance of interference-constrained secondary users in an underlay cognitive radio (CR) network. However, unlike conventional relaying, the state of the links between the relay and the primary receiver affects the choice of the relay. Further, while the optimal amplify-and-forward (AF) relay selection rule for underlay CR is well understood for the peak interference-constraint, this is not so for the less conservative average interference constraint. For the latter, we present three novel AF relay selection (RS) rules, namely, symbol error probability (SEP)-optimal, inverse-of-affine (IOA), and linear rules. We analyze the SEPs of the IOA and linear rules and also develop a novel, accurate approximation technique for analyzing the performance of AF relays. Extensive numerical results show that all the three rules outperform several RS rules proposed in the literature and generalize the conventional AF RS rule.

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In this paper, we study two multi-dimensional Goodness-of-Fit tests for spectrum sensing in cognitive radios. The multi-dimensional scenario refers to multiple CR nodes, each with multiple antennas, that record multiple observations from multiple primary users for spectrum sensing. These tests, viz., the Interpoint Distance (ID) based test and the h, f distance based tests are constructed based on the properties of stochastic distances. The ID test is studied in detail for a single CR node case, and a possible extension to handle multiple nodes is discussed. On the other hand, the h, f test is applicable in a multi-node setup. A robustness feature of the KL distance based test is discussed, which has connections with Middleton's class A model. Through Monte-Carlo simulations, the proposed tests are shown to outperform the existing techniques such as the eigenvalue ratio based test, John's test, and the sphericity test, in several scenarios.

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Nanoparticle deposition behavior observed at the Darcy scale represents an average of the processes occurring at the pore scale. Hence, the effect of various pore-scale parameters on nanoparticle deposition can be understood by studying nanoparticle transport at pore scale and upscaling the results to the Darcy scale. In this work, correlation equations for the deposition rate coefficients of nanoparticles in a cylindrical pore are developed as a function of nine pore-scale parameters: the pore radius, nanoparticle radius, mean flow velocity, solution ionic strength, viscosity, temperature, solution dielectric constant, and nanoparticle and collector surface potentials. Based on dominant processes, the pore space is divided into three different regions, namely, bulk, diffusion, and potential regions. Advection-diffusion equations for nanoparticle transport are prescribed for the bulk and diffusion regions, while the interaction between the diffusion and potential regions is included as a boundary condition. This interaction is modeled as a first-order reversible kinetic adsorption. The expressions for the mass transfer rate coefficients between the diffusion and the potential regions are derived in terms of the interaction energy profile. Among other effects, we account for nanoparticle-collector interaction forces on nanoparticle deposition. The resulting equations are solved numerically for a range of values of pore-scale parameters. The nanoparticle concentration profile obtained for the cylindrical pore is averaged over a moving averaging volume within the pore in order to get the 1-D concentration field. The latter is fitted to the 1-D advection-dispersion equation with an equilibrium or kinetic adsorption model to determine the values of the average deposition rate coefficients. In this study, pore-scale simulations are performed for three values of Peclet number, Pe = 0.05, 5, and 50. We find that under unfavorable conditions, the nanoparticle deposition at pore scale is best described by an equilibrium model at low Peclet numbers (Pe = 0.05) and by a kinetic model at high Peclet numbers (Pe = 50). But, at an intermediate Pe (e.g., near Pe = 5), both equilibrium and kinetic models fit the 1-D concentration field. Correlation equations for the pore-averaged nanoparticle deposition rate coefficients under unfavorable conditions are derived by performing a multiple-linear regression analysis between the estimated deposition rate coefficients for a single pore and various pore-scale parameters. The correlation equations, which follow a power law relation with nine pore-scale parameters, are found to be consistent with the column-scale and pore-scale experimental results, and qualitatively agree with the colloid filtration theory. These equations can be incorporated into pore network models to study the effect of pore-scale parameters on nanoparticle deposition at larger length scales such as Darcy scale.

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Cooperative relaying combined with selection exploits spatial diversity to significantly improve the performance of interference-constrained secondary users in an underlay cognitive radio network. We present a novel and optimal relay selection (RS) rule that minimizes the symbol error probability (SEP) of an average interference-constrained underlay secondary system that uses amplify-and-forward relays. A key point that the rule highlights for the first time is that, for the average interference constraint, the signal-to-interference-plus-noise-ratio (SINR) of the direct source-to-destination (SI)) link affects the choice of the optimal relay. Furthermore, as the SINR increases, the odds that no relay transmits increase. We also propose a simpler, more practical, and near-optimal variant of the optimal rule that requires just one bit of feedback about the state of the SD link to the relays. Compared to the SD-unaware ad hoc RS rules proposed in the literature, the proposed rules markedly reduce the SEP by up to two orders of magnitude.