236 resultados para ripple


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Micromagnetic ripple structures on the surfaces of thick specimens of ultra-soft magnetic material having strong surface anisotropy Ks favouring out-of-surface magnetization have been calculated. These ripples have wavelengths of the order of 0.1 μm and extend to a depth ∼ √A/Ms, where A is the exchange constant and Ms is the saturation magnetization. The wave-vectors of the ripple structures are either transverse or parallel to the bulk magnetization. Both structures have lower energy than the one-dimensional structure discussed by O'Handley and Woods, and they exhibit stronger normal magnetization. The transverse structure requires a surface anisotropy Ks ≥ 0.80K0, where is that required for the one-dimensional structure. The threshold for longitudinal ripples is 0.84K0. It is suggested that the transverse structure probably constitutes the ground state. The magnitudes of Ks and A should be obtainable from measurements of the ripple wavelength and amplitude, and Ms.

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One of the key challenges in geographic routing is how to deal with dead-ends, where greedy routing fails to find a neighbor node which is closer to the destination. Most existing geographic routing algorithms just switch to the deterministic face routing or limits its face searching range. In this paper, we demonstrate that we can improve routing performance by considering local connectivity status at each node before making routing decision. We present a protocol, Density Ripple Exchange (DRE), that maintains local density information at each node, and a new geographic routing algorithm, Geographic Ripple Routing (GRR), that achieves better routing performance in both hop stretch and transmission stretch than existing geographic routing algorithms by exploiting available connectivity information. Our simulations demonstrate that we increased the performance for GRR over Greedy Perimeter Stateless Routing (GPSR) by about 15%. The cost of this improved performance is a small amount of additional local connectivity information required for our algorithm.

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The differences in economy, society, demography and geography in different regions are main reasons which cause disparities in regional house prices. Three theories, namely ripple effect hypothesis, convergence and efficient market hypothesis, are used to examine price fluctuations in spatial dimension amongst eight housing markets in Australian state capital cities.

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Purpose: Studies into ripple effects have previously focused on the interconnections between house price movements across cities over space and time. These interconnections were widely investigated in previous research using vector autoregression models. However, the effects generated from spatial information could not be captured by conventional vector autoregression models. This research aimed to incorporate spatial lags into a vector autoregression model to illustrate spatial-temporal interconnections between house price movements across the Australian capital cities. Design/methodology/approach: Geographic and demographic correlations were captured by assessing geographic distances and demographic structures between each pair of cities, respectively. Development scales of the housing market were also used to adjust spatial weights. Impulse response functions based on the estimated SpVAR model were further carried out to illustrate the ripple effects. Findings: The results confirmed spatial correlations exist in housing price dynamics in the Australian capital cities. The spatial correlations are dependent more on the geographic rather than the demographic information. Originality/value: This research investigated the spatial heterogeneity and autocorrelations of regional house prices within the context of demographic and geographic information. A spatial vector autoregression model was developed based on the demographic and geographic distance. The temporal and spatial effects on house prices in Australian capital cities were then depicted.

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This paper explores firstly the potential of a new evolutionary method - the Cross-Entropy (CE) method in solving continuous inverse electromagnetic problems. For this purpose, an adaptive updating formula for the smoothing parameter, some mutation operation, and a new termination criterion are proposed. The proposed CE based metaheuristics is applied to reduce the ripple of the magnetic levitation forces of a prototype Maglev system. The numerical results have shown that the ripple of the magnetic levitation forces of the prototype system is reduced significantly after the design optimization using the proposed algorithm.

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This paper presents a method for electromagnetic torque ripple and copper losses reduction in (non-sinusoidal or trapezoidal) surface-mount permanent magnet synchronous machines (SM-PMSM). The method is based on an extension of classical dq transformation that makes it possible to write a vectorial model for this kind of machine (with a non-sinusoidal back-EMF waveform). This model is obtained by the application of that transformation in the classical machine per-phase model. That transformation can be applied to machines that have any type of back-EMF waveform, and not only trapezoidal or square-wave back-EMF waveforms. Implementation results are shown for an electrical converter, using the proposed vectorial model, feeding a non-sinusoidal synchronous machine (brushless DC motor). They show that the use of this vectorial mode is a way to achieve improvements in the performance of this kind of machine, considering the electromagnetic torque ripple and copper losses, if compared to a drive system that employs a classical six-step mode as a converter. Copyright (C) 2011 John Wiley & Sons, Ltd.

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Analysis of the peak-to-peak output current ripple amplitude for multiphase and multilevel inverters is presented in this PhD thesis. The current ripple is calculated on the basis of the alternating voltage component, and peak-to-peak value is defined by the current slopes and application times of the voltage levels in a switching period. Detailed analytical expressions of peak-to-peak current ripple distribution over a fundamental period are given as function of the modulation index. For all the cases, reference is made to centered and symmetrical switching patterns, generated either by carrier-based or space vector PWM. Starting from the definition and the analysis of the output current ripple in three-phase two-level inverters, the theoretical developments have been extended to the case of multiphase inverters, with emphasis on the five- and seven-phase inverters. The instantaneous current ripple is introduced for a generic balanced multiphase loads consisting of series RL impedance and ac back emf (RLE). Simplified and effective expressions to account for the maximum of the output current ripple have been defined. The peak-to-peak current ripple diagrams are presented and discussed. The analysis of the output current ripple has been extended also to multilevel inverters, specifically three-phase three-level inverters. Also in this case, the current ripple analysis is carried out for a balanced three-phase system consisting of series RL impedance and ac back emf (RLE), representing both motor loads and grid-connected applications. The peak-to-peak current ripple diagrams are presented and discussed. In addition, simulation and experimental results are carried out to prove the validity of the analytical developments in all the cases. The cases with different phase numbers and with different number of levels are compared among them, and some useful conclusions have been pointed out. Furthermore, some application examples are given.

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We examine the time-series relationship between housing prices in Los Angeles, Las Vegas, and Phoenix. First, temporal Granger causality tests reveal that Los Angeles housing prices cause housing prices in Las Vegas (directly) and Phoenix (indirectly). In addition, Las Vegas housing prices cause housing prices in Phoenix. Los Angeles housing prices prove exogenous in a temporal sense and Phoenix housing prices do not cause prices in the other two markets. Second, we calculate out-of-sample forecasts in each market, using various vector autoregessive (VAR) and vector error-correction (VEC) models, as well as Bayesian, spatial, and causality versions of these models with various priors. Different specifications provide superior forecasts in the different cities. Finally, we consider the ability of theses time-series models to provide accurate out-of-sample predictions of turning points in housing prices that occurred in 2006:Q4. Recursive forecasts, where the sample is updated each quarter, provide reasonably good forecasts of turning points.

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Advanced control techniques like V2, Vout hysteresis or V2Ic can strongly reduce the required output capacitance in PowerSoC converters. Techniques to analyze power converters based on the analysis of the frequency response are not suitable for ripple-based controllers that use fast-scale dynamics to control the power stage. This paper proves that the use of discrete modeling together with Floquet theory is a very powerful tool to model the system and derive stable region diagrams for sensitivity analysis. It is applied to V 2Ic control, validating experimentally that Floquet theory predicts accurately subharmonic oscillations. This method is applied to several ripplebased controllers, providing higher accuracy when it is compared with other techniques based on the frequency response. The paper experimentally validates the usefulness of the discrete modeling and the Floquet theory on a 5 MHz Buck converter with a V 2Ic control.