333 resultados para twice line frequency
Resumo:
We report high pressure Raman studies on single crystals of metallic LaB6 upto a pressure of 16.$ GPa. Raman spectra shows three lines at 680 cm(-1) (T-2g), 1120 cm(-1) (E-g) and 1258 cm(-1) (A(1g)), associated with the internal modes of B-6 molecule. The T-2g mode shows an asymmetric Fano line shape, arising from the interference between the phonon line and the electronic continuum. The line is fitted with I(omega) = I-0(q + epsilon(2))/(I + epsilon(2)) where epsilon = (omega - omega(0))/Gamma, omega(0) is the phonon frequency renormalised due to electron-phonon self energy corrections, Tis the width parameter proportional to the square of the matrix element of the electron-phonon interaction potential. The parameter a signifies the strength of interference. Most interestingly our pressure data for the T-2g mode shows a significant change in the slope of the mode frequency with pressure d omega(0)/dP and Gamma at 9.5 GPa. This clearly indicates that LaB6 undergoes a subtle phase transition at 9.5 GPa within the metallic phase.
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In this paper we report resonance Raman scattering from graphite covering excitation energies in the range 2.4 eV to 6 eV. The Raman excitation profile shows a maximum at 4.94 eV (lambda = 251nm) for the G - band (1582 cm(-1)). The D-band at similar to 1350 cm(-1), attributed to disorder activated Raman scattering, does not show up in Raman spectra recorded with excitation wavelengths smaller than 257.3 nm, revealing that the resonance enhancements of the G and D-modes are widely different. Earlier Raman measurements in carbon materials have also revealed a very large and unusual dependence of the D - mode frequency on excitation laser wavelength. This phenomenon is also observed in carbon nanotubes. In this paper we show for the first time that the above unusual dependence arises from the disorder - induced double resonance mechanism.
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Summary form only given. A scheme for code compression that has a fast decompression algorithm, which can be implemented using simple hardware, is proposed. The effectiveness of the scheme on the TMS320C62x architecture that includes the overheads of a line address table (LAT) is evaluated and obtained compression rates ranging from 70% to 80%. Two schemes for decompression are proposed. The basic idea underlying the scheme is a simple clustering algorithm that partially maps a block of instructions into a set of clusters. The clustering algorithm is a greedy algorithm based on the frequency of occurrence of various instructions.
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This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.
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We present a timing and broad-band pulse-phase-resolved spectral analysis of the transient Be X-ray binary pulsar 1A 1118-61 observed during its outburst in 2009 January using Suzaku observations. The Suzaku observations were made twice, once at the peak of the outburst, and the other 13 d later at its declining phase. Pulse profiles from both observations exhibit strong energy dependence with several peaks at low energies and a single peak above similar to 10 keV. A weak, narrow peak is detected at the main dip of the pulse profiles from both observations in the energy bands below 3 keV, indicating the presence of a phase-dependent soft excess in the source continuum. The broad-band energy spectrum of the pulsar could be fitted well with a partial covering cut-off power-law model and a narrow iron fluorescence line. We also detect a broad cyclotron feature at similar to 50 keV from both observations which is a feature common for accretion-powered pulsars with high magnetic field strength. The pulse-phase-resolved spectral analysis shows an increase in the absorption column density of the partial covering component, as well as variation in the covering fraction at the dips of the pulse profiles, which naturally explains energy dependence of the same. The cyclotron line parameters also show significant variation with pulse phase with an similar to 10 keV variation in the cyclotron line energy and a variation in depth by a factor of 3. This can be explained either as the effect of different viewing angles of the dipole field at different pulse phases, or due to a more complex underlying magnetic field geometry.
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This paper presents the development of a neural network based power system stabilizer (PSS) designed to enhance the damping characteristics of a practical power system network representing a part of Electricity Generating Authority of Thailand (EGAT) system. The proposed PSS consists of a neuro-identifier and a neuro-controller which have been developed based on functional link network (FLN) model. A recursive on-line training algorithm has been utilized to train the two neural networks. Simulation results have been obtained under various operating conditions and severe disturbance cases which show that the proposed neuro-PSS can provide a better damping to the local as well as interarea modes of oscillations as compared to a conventional PSS
Resumo:
In this paper, knowledge-based approach using Support Vector Machines (SVMs) are used for estimating the coordinated zonal settings of a distance relay. The approach depends on the detailed simulation studies of apparent impedance loci as seen by distance relay during disturbance, considering various operating conditions including fault resistance. In a distance relay, the impedance loci given at the relay location is obtained from extensive transient stability studies. SVMs are used as a pattern classifier for obtaining distance relay co-ordination. The scheme utilizes the apparent impedance values observed during a fault as inputs. An improved performance with the use of SVMs, keeping the reach when faced with different fault conditions as well as system power flow changes, are illustrated with an equivalent 265 bus system of a practical Indian Western Grid.
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Since the end of second world war, extra high voltage ac transmission has seen its development. The distances between generating and load centres as well as the amount of power to be handled increased tremendously for last 50 years. The highest commercial voltage has increased to 765 kV in India and 1,200 kV in many other countries. The bulk power transmission has been mostly performed by overhead transmission lines. The dual task of mechanically supporting and electrically isolating the live phase conductors from the support tower is performed by string insulators. Whether in clean condition or under polluted conditions, the electrical stress distribution along the insulators governs the possible flashover, which is quite detrimental to the system. Hence the present investigation aims to study accurately, the field distribution for various types of porcelain/ceramic insulators (Normal and Antifog discs) used for high-voltage transmission. The surface charge simulation method is employed for the field computation. A comparison on normalised surface resistance, which is an indicator for the stress concentration under polluted condition, is also attempted.
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The propagation of axial waves in hyperelastic rods is studied using both time and frequency domain finite element models. The nonlinearity is introduced using the Murnaghan strain energy function and the equations governing the dynamics of the rod are derived assuming linear kinematics. In the time domain, the standard Galerkin finite element method, spectral element method, and Taylor-Galerkin finite element method are considered. A frequency domain formulation based on the Fourier spectral method is also developed. It is found that the time domain spectral element method provides the most efficient numerical tool for the problem considered.
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A flexible composite suitable for MHz frequency application has been developed by combining Fe3O4 and polyvinyl alcohol (PVA). The loss factor and the permeability have been evaluated. At an optimum weight percentage of Fe3O4 in the PVA matrix, the frequency at which the loss factor gives a minimum shifts to the MHz region. The loss factor has been found to be lower by one order of magnitude at 70 MHz compared to the presently used nickel zinc ferrite. The Henkel plot and the Cole-Cole plot have been obtained for the understanding of the high magnetic permeability and the low loss factor. (C) 2012 American Institute of Physics. doi:10.1063/1.3672867]
Resumo:
SrRuO3 is a well-known itinerant ferromagnet with many intriguing characteristics. The Ru deficiency in this system is believed to play a pivotal role in influencing many of its magnetic and transport properties. The present study involves the magnetic and transport properties of the Ru-deficient SrRu0.93O3 sample to gain more insight into the unusual low-temperature behavior. The ac susceptibility study reveals a sharp ferromagnetic transition at 150 K followed by a hump at T-h similar to 50 K, which has anomalous frequency dependence. Besides, the T-h shifts to lower temperatures with an increase in the superposed dc-biasing field and adheres to H-2 dependence, in accordance with the Gabay and Toulouse line for the Heisenberg spin glass systems. We also observe a pronounced memory effect toward the low-temperature side, signifying the characteristic of glassy behavior. The temperature-dependent magnetoresistance indicates the signature of an additional ordering toward the low-temperature side. All of the interesting findings combined unveil the existence of low-temperature cryptic magnetic phase in SrRu0.93O3. (C) 2012 American Institute of Physics. doi:10.1063/1.3673427]