978 resultados para Rotating electrical machine


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An analysis is developed to study the unsteady mixed convection flow over a vertical cone rotating in an ambient fluid with a time-dependent angular velocity in the presence of a magnetic field. The coupled nonlinear partial differential equations governing the flow have been solved numerically using an implicit finite-difference scheme. The local skin friction coefficients in the tangential and azimuthal directions and the local Nusselt number increase with the time when the angular velocity of the-cone increases, but the reverse trend is observed for decreasing angular velocity. However, these are not mirror reflection of each other. The magnetic field reduces the skin friction coefficient in the tangential direction and also the Nusselt number, but it increases the skin friction coefficient in the azimuthal direction. The skin friction coefficients and the Nusselt number increase with the buoyancy force.

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The unsteady rotating flow of a laminar incompressible viscous electrically conducting fluid over a rotating sphere in the vicinity of the equator has been studied. The fluid and the body rotate either in the same direction or in opposite directions. The effects of surface suction and magnetic field have been included in the analysis. There is an initial steady state that is perturbed by a sudden change in the rotational velocity of the sphere, and this causes unsteadiness in the flow field. The nonlinear coupled parabolic partial differential equations governing the boundary-layer flow have been solved numerically by using an implicit finite-difference scheme. For large suction or magnetic field, analytical solutions have also been obtained. The magnitude of the radial, meridional and rotational velocity components is found to be higher when the fluid and the body rotate in opposite directions than when they rotate in the same direction. The surface shear stresses in the meridional and rotational directions change sign when the ratio of the angular velocities of the sphere and the fluid lambda greater than or equal to lambda(0). The final (new) steady state is reached rather quickly which implies that the spin-up time is small. The magnetic field and surface suction reduce the meridional shear stress, but increase the surface shear stress in the rotational direction.

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Load commutated inverter (LCI)-fed wound field synchronous motor drives are used for medium-voltage high-power drive applications. This drive suffers from drawbacks such as complex starting procedure, sixth harmonic torque pulsations, quasi square wave motor current, notches in the terminal voltages, etc. In this paper, a hybrid converter circuit, consisting of an LCI and a voltage source inverter (VSI), is proposed, which can be a universal high-power converter solution for wound field synchronous motor drives. The proposed circuit, with the addition of a current-controlled VSI, overcomes nearly all of the shortcomings present in the conventional LCI-based system besides providing many additional advantages. In the proposed drive, the motor voltage and current are always sinusoidal even with the LCI switching at the fundamental frequency. The performance of the drive is demonstrated with detailed experimental waveforms from a 15.8-hp salient pole wound field synchronous machine. Finally, a brief description of the control scheme used for the proposed circuit is given.

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Zinc oxide (ZnO) thin films have been prepared on silicon substrates by sol-gel spin coating technique with spinning speed of 3,000 rpm. The films were annealed at different temperatures from 200 to 500 A degrees C and found that ZnO films exhibit different nanostructures at different annealing temperatures. The X-ray diffraction (XRD) results showed that the ZnO films convert from amorphous to polycrystalline phase after annealing at 400 A degrees C. The metal oxide semiconductor (MOS) capacitors were fabricated using ZnO films deposited on pre-cleaned silicon (100) substrates and electrical properties such as current versus voltage (I-V) and capacitance versus voltage (C-V) characteristics were studied. The electrical resistivity decreased with increasing annealing temperature. The oxide capacitance was measured at different annealing temperatures and different signal frequencies. The dielectric constant and the loss factor (tan delta) were increased with increase of annealing temperature.

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This paper makes an attempt to assess the benefits of replacing a conventional generator excitation system (AVR + PSS) with a nonlinear voltage regulator using the concepts of synchronizing and damping torque components in a single machine infinite bus (SMIB) system. In recent years, there has been considerable interest in designing nonlinear excitation controllers, which are expected to give better dynamic performance over a wider range of system and operating conditions. The performance of these controllers is often justified by simulation studies on few test cases which may not adequately represent the diverse operating conditions of a typical power system. The performance of two such nonlinear controllers which are designed based on feedback linearization and include automatic voltage regulation with good dynamic performance have been analyzed using an SMIB model. Linearizing the nonlinear control laws along with the SMIB system equations, a Heffron Phillip's type of a model has been derived. Concepts of synchronizing and damping torque components have been used to show that such controllers can impair the small signal stability under certain operating conditions. This paper shows the possibility of negative damping contribution due to nonlinear voltage regulators and gives a new insight on understanding the physical impact of complex nonlinear control laws on power system dynamics.

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Cobalt and iron nanoparticles are doped in carbon nanotube (CNT)/polymer matrix composites and studied for strain and magnetic field sensing properties. Characterization of these samples is done for various volume fractions of each constituent (Co and Fe nanoparticles and CNTs) and also for cases when only either of the metallic components is present. The relation between the magnetic field and polarization-induced strain are exploited. The electronic bandgap change in the CNTs is obtained by a simplified tight-binding formulation in terms of strain and magnetic field. A nonlinear constitutive model of glassy polymer is employed to account for (1) electric bias field dependent softening/hardening (2) CNT orientations as a statistical ensemble and (3) CNT volume fraction. An effective medium theory is then employed where the CNTs and nanoparticles are treated as inclusions. The intensity of the applied magnetic field is read indirectly as the change in resistance of the sample. Very small magnetic fields can be detected using this technique since the resistance is highly sensitive to strain. Its sensitivity due to the CNT volume fraction is also discussed. The advantage of this sensor lies in the fact that it can be molded into desirable shape and can be used in fabrication of embedded sensors where the material can detect external magnetic fields on its own. Besides, the stress-controlled hysteresis of the sample can be used in designing memory devices. These composites have potential for use in magnetic encoders, which are made of a magnetic field sensor and a barcode.

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In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 sq.km. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, ordinary kriging and Support Vector Machine (SVM) models have been developed. In ordinary kriging, the knowledge of the semivariogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of Bangalore, where field measurements are not available. A cross validation (Q1 and Q2) analysis is also done for the developed ordinary kriging model. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing e-insensitive loss function has been used to predict the reduced level of rock from a large set of data. A comparison between ordinary kriging and SVM model demonstrates that the SVM is superior to ordinary kriging in predicting rock depth.