956 resultados para dynamic analysis


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Theory is presented for simulating the dynamic wheel forces generated by heavy road vehicles and the resulting dynamic response of road surfaces to these loads. Sample calculations are provided and the vehicle simulation is validated with data from full-scale tests. The methods are used in the accompanying paper to simulate the road damage done by a tandem-axle vehicle.

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The Brushless Doubly-Fed Induction Generator (BDFIG) shows commercial promise as replacement for doublyfed slip-ring generators for wind power applications by offering reduced capital and operational costs due to its brushless operation. In order to facilitate its commercial deployment, the capabilities of the BDFIG system to comply with grid code requirements have to be assessed. This paper, for the first time, studies the performance of the BDFIG under grid fault ride-through and presents the dynamic behaviour of the machine during three-phase symmetrical voltage dips. Both full and partial voltage dips are studied using a vector model. Simulation and experimental results are provided for a 180 frame BDFIG.

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A quasi-thermodynamic model of metalorganic vapor phase epitaxy (MOVPE) growth of GaxAlyIn1-x-yN alloys has been proposed. In view of the complex growth behavior of GaxAlyIn1-x-yN, we focus our attention on the galliumrich quaternary alloys that are lattice matched to GaN, In0.15Ga0.85N or Al0.15Ga0.85N, which are widely used in the GaN-based optoelectronic devices. The relationship between GaAlInN alloy composition and input molar ratio of group III metalorganic compounds at various growth conditions has been calculated. The influence of growth temperature, nitrogen fraction in the carrier gas, input partial pressure of group III metalorganics, reactor pressure, V/III ratio and the decomposition rate of ammonia on the composition of deposited alloys are studied systematically. Based on these calculated results, we can find out the appropriate growth conditions for the MOVPE growth of GaxAlyIn1-x-yN alloy lattice matched to GaN, In0.15Ga0.85N or Al0.15Ga0.85N. (C) 2002 Elsevier Science B.V. All rights reserved.

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This paper uses dynamic impulse response analysis to investigate the interrelationships among stock price volatility, trading volume, and the leverage effect. Dynamic impulse response analysis is a technique for analyzing the multi-step-ahead characteristics of a nonparametric estimate of the one-step conditional density of a strictly stationary process. The technique is the generalization to a nonlinear process of Sims-style impulse response analysis for linear models. In this paper, we refine the technique and apply it to a long panel of daily observations on the price and trading volume of four stocks actively traded on the NYSE: Boeing, Coca-Cola, IBM, and MMM.

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An electrolytic cell for Aluminum production contains molten metal subject to high currents and magnetic flux density. The interaction between these two fields creates electromagnetic forces within the liquid metal and can generate oscillations of the fluid similar to the waves at the free surface of oceans and rivers. The study of this phenomenon requires the simulation of the current density field, of the magnetic flux density field and the solution of the equations of motion of the liquid mass. An attempt to analyze the dynamical behavior of this problem is made by coupling different codes, based on different numerical techniques, in a single tool. The simulations are presented and discussed.

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Self-alignment of soldered electronic components such as flip-chips (FC), ball grid arrays (BGA) and optoelectronic devices during solder reflow is important as it ensures good alignment between components and substrates. Two uncoupled analytical models are presented which provide estimates of the dynamic time scales of both the chip and the solder in the self-alignment process. These predicted time scales can be used to decide whether a coupled dynamic analysis is required for the analysis of the chip motion. In this paper, we will show that for flip-chips, the alignment dynamics can be described accurately only when the chip motion is coupled with the solder motion because the two have similar time-scale values. To study this coupled phenomenon, a dynamic modeling method has been developed. The modeling results show that the uncoupled and coupled calculations result in significantly different predictions. The calculations based on the coupled model predict much faster rates of alignment than those predicted using the uncoupled approach.

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The paper presents a dynamic study of the Spanish labour market which tries to determine if it matches the characteristics of transitional labour markets from a fl exicurity approach. Employment trajectories of Spanish workers during the years 2007-2010 are studied using the Continuous Sample of Working Lives. This period covers the end of the expansion of the Spanish economy and the beginning of the current employment crisis. From the combination of the chosen topic, the approach, and the database used, this is a novel perspective in our country. The article shows evidence of the evolution of the employment and unemployment spells, the Spanish labour market turnover degree, and the diffi culties of some groups for carrying out transition between employment and unemployment. The results obtained show a labour market in which a) transitions have come to a halt, and b) there is high job insecurity.

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This paper analyses earthquake data in the perspective of dynamical systems and its Pseudo Phase Plane representation. The seismic data is collected from the Bulletin of the International Seismological Centre. The geological events are characterised by their magnitude and geographical location and described by means of time series of sequences of Dirac impulses. Fifty groups of data series are considered, according to the Flinn-Engdahl seismic regions of Earth. For each region, Pearson’s correlation coefficient is used to find the optimal time delay for reconstructing the Pseudo Phase Plane. The Pseudo Phase Plane plots are then analysed and characterised.

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This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

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This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.