877 resultados para Model-based geostatistics


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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We consider a gauge model based on a SU(3)XU(1) symmetry in which the lepton number is violated explicitly by charged scalar and gauge bosons, including a vector field with double electric

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The phenomenology of a QCD-Pomeron model based on the exchange of a pair of non-perturbative gluons, i.e. gluon fields with a finite correlation length in the vacuum, is studied in comparison with the phenomenology of QCD chiral symmetry breaking, based on non-perturbative solutions of Schwinger-Dyson equations for the quark propagator including these non-perturbative gluon effects. We show that these models are incompatible, and point out some possibles origins of this problem.

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In the context of the standard model the quantization of the electric charge occurs only family by family. When we consider the three families together with massless neutrinos the electric charge is not quantized any more. Here we show that a chiral bilepton gauge model based on the gauge group SU(3)C ⊗ SU(3)L ⊗ U(1)N explains the quantization of the electric charge when we take into account the three families of fermions. This result does not depend on the neutrino masses. Charge quantization occurs whether the neutrinos are massless or Dirac or Majorana massive fields.

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The non-linear electrical properties of CoO-doped and Nb205-doped SnO2 ceramics were characterized. X-ray diffraction and scanning electron microscopy indicated that the system is single phase. The electrical conduction mechanism for low applied electrical field was associated with thermionic emission of the Schottky type. An atomic defect model based on the Schottky double-barrier formation was proposed to explain the origin of the potential barrier at the ceramic grain boundaries. These defects create depletion layers at grain boundaries, favouring electron tunnelling at high values of applied electrical field. © 1998 Chapman & Hall.

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This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically >30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, multiple sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with experimental examples, investigations on a massive quarter scale model of a steel bridge section and a space truss structure, in order to verify the performance of this proposed methodology.

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A nonthermal quantum mechanical statistical fragmentation model based on tunneling of particles through potential barriers is studied in compact two- and three-dimensional systems. It is shown that this fragmentation dynamics gives origin to several static and dynamic scaling relations. The critical exponents are found and compared with those obtained in classical statistical models of fragmentation of general interest, in particular with thermal fragmentation involving classical processes over potential barriers. Besides its general theoretical interest, the fragmentation dynamics discussed here is complementary to classical fragmentation dynamics of interest in chemical kinetics and can be useful in the study of a number of other dynamic processes such as nuclear fragmentation. ©2000 The American Physical Society.

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Water waves generated by landslides were long menace in certain localities and the study of this phenomenon were carried out at an accelerated rate in the last decades. Nevertheless, the phase of wave creation was found to be very complex. As such, a numerical model based on Boussinesq equations was used to describe water waves generated by local disturbance. This numerical model takes in account the vertical acceleration of the particles and considers higher orders derivate terms previously neglected by Boussinesq, so that in the generation zone, this model can support high relative amplitude of waves.

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Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.

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In this work a new method is proposed of separated estimation for the ARMA spectral model based on the modified Yule-Walker equations and on the least squares method. The proposal of the new method consists of performing an AR filtering in the random process generated obtaining a new random estimate, which will reestimate the ARMA model parameters, given a better spectrum estimate. Some numerical examples will be presented in order to ilustrate the performance of the method proposed, which is evaluated by the relative error and the average variation coefficient.

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A correction procedure based on digital signal processing theory is proposed to smooth the numeric oscillations in electromagnetic transient simulation results from transmission line modeling based on an equivalent representation by lumped parameters. The proposed improvement to this well-known line representation is carried out with an Finite Impulse Response (FIR) digital filter used to exclude the high-frequency components associated with the spurious numeric oscillations. To prove the efficacy of this correction method, a well-established frequency-dependent line representation using state equations is modeled with an FIR filter included in the model. The results obtained from the state-space model with and without the FIR filtering are compared with the results simulated by a line model based on distributed parameters and inverse transforms. Finally, the line model integrated with the FIR filtering is also tested and validated based on simulations that include nonlinear and time-variable elements. © 2012 Elsevier Ltd. All rights reserved.

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This article shows a transmission line model developed directly in the phase domain. The proposed model is based on the relationships between the phase currents and voltages at both the sending and receiving ends of a single-phase line. These relationships, established using an ABCD matrix, were extended to multi-phase lines. The proposed model was validated by using it to represent a transmission line during short-and open-circuit tests. The results obtained with the proposed model were compared with results obtained with a classical model based on modal decomposition. These comparisons show that proposed model was correctly developed. © 2013 Taylor and Francis Group, LLC.

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Models of different degrees of complexity are found in the literature for the estimation of lightning striking distances and attractive radius of objects and structures. However, besides the oversimplifications of the physical nature of the lightning discharge on which most of them are based, till recently the tridimensional structure configuration could not be considered. This is an important limitation, as edges and other details of the object affect the electric field and, consequently, the upward leader initiation. Within this context, the Self-consistent leader initiation and propagation model (SLIM) proposed by Becerra and Cooray is state-of-the-art leader inception and propagation leader model based on the physics of leader discharges which enables the tridimensional geometry of the structure to be taken into account. In this paper, the model is used for estimating the striking distance and attractive radius of power transmission lines. The results are compared with those obtained from the electrogeometric and Eriksson's models. © 2003-2012 IEEE.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)