Sistemas Nanoestruturados: Heteroestruturas Quasi-Periódicas de Nitretos e Cálculos Ab initio em Polimorfos CaCO3

The physical properties and the excitations spectrum in oxides and semiconductors materials are presented in this work, whose the first part presents a study on the confinement of optical phonons in artificial systems based on III-V nitrides, grown in periodic and quasiperiodic forms. The second part of this work describes the Ab initio calculations which were carried out to obtain the optoeletronic properties of Calcium Oxide (CaO) and Calcium Carbonate (CaCO3) crystals. For periodic and quasi-periodic superlattices, we present some dynamical properties related to confined optical phonons (bulk and surface), obtained through simple theories, such as the dielectric continuous model, and using techniques such as the transfer-matrix method. The localization character of confined optical phonon modes, the magnitude of the bands in the spectrum and the power laws of these structures are presented as functions of the generation number of sequence. The ab initio calculations have been carried out using the CASTEP software (Cambridge Total Sequential Energy Package), and they were based on ultrasoft-like pseudopotentials and Density Functional Theory (DFT). Two di®erent geometry optimizations have been e®ectuated for CaO crystals and CaCO3 polymorphs, according to LDA (local density approximation) and GGA (generalized gradient approximation) approaches, determining several properties, e. g. lattice parameters, bond length, electrons density, energy band structures, electrons density of states, e®ective masses and optical properties, such as dielectric constant, absorption, re°ectivity, conductivity and refractive index. Those results were employed to investigate the confinement of excitons in spherical Si@CaCO3 and CaCO3@SiO2 quantum dots and in calcium carbonate nanoparticles, and were also employed in investigations of the photoluminescence spectra of CaCO3 crystal

Novo método para estimativa do gradiente de fratura para poços de petróleo

The development of oil wells drilling requires additional cares mainly if the drilling is in offshore ultra deep water with low overburden pressure gradients which cause low fracture gradients and, consequently, difficult the well drilling by the reduction of the operational window. To minimize, in the well planning phases, the difficulties faced by the drilling in those sceneries, indirect models are used to estimate fracture gradient that foresees approximate values for leakoff tests. These models generate curves of geopressures that allow detailed analysis of the pressure behavior for the whole well. Most of these models are based on the Terzaghi equation, just differentiating in the determination of the values of rock tension coefficient. This work proposes an alternative method for prediction of fracture pressure gradient based on a geometric correlation that relates the pressure gradients proportionally for a given depth and extrapolates it for the whole well depth, meaning that theses parameters vary in a fixed proportion. The model is based on the application of analytical proportion segments corresponding to the differential pressure related to the rock tension. The study shows that the proposed analytical proportion segments reaches values of fracture gradient with good agreement with those available for leakoff tests in the field area. The obtained results were compared with twelve different indirect models for fracture pressure gradient prediction based on the compacting effect. For this, a software was developed using Matlab language. The comparison was also made varying the water depth from zero (onshore wellbores) to 1500 meters. The leakoff tests are also used to compare the different methods including the one proposed in this work. The presented work gives good results for error analysis compared to other methods and, due to its simplicity, justify its possible application

Critério de correntropia no treinamento de redes fuzzy wavelet neural networks para identificação de sistemas dinâmicos não lineares

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.

Novo método para estimativa do gradiente de fratura para poços de petróleo

The development of oil wells drilling requires additional cares mainly if the drilling is in offshore ultra deep water with low overburden pressure gradients which cause low fracture gradients and, consequently, difficult the well drilling by the reduction of the operational window. To minimize, in the well planning phases, the difficulties faced by the drilling in those sceneries, indirect models are used to estimate fracture gradient that foresees approximate values for leakoff tests. These models generate curves of geopressures that allow detailed analysis of the pressure behavior for the whole well. Most of these models are based on the Terzaghi equation, just differentiating in the determination of the values of rock tension coefficient. This work proposes an alternative method for prediction of fracture pressure gradient based on a geometric correlation that relates the pressure gradients proportionally for a given depth and extrapolates it for the whole well depth, meaning that theses parameters vary in a fixed proportion. The model is based on the application of analytical proportion segments corresponding to the differential pressure related to the rock tension. The study shows that the proposed analytical proportion segments reaches values of fracture gradient with good agreement with those available for leakoff tests in the field area. The obtained results were compared with twelve different indirect models for fracture pressure gradient prediction based on the compacting effect. For this, a software was developed using Matlab language. The comparison was also made varying the water depth from zero (onshore wellbores) to 1500 meters. The leakoff tests are also used to compare the different methods including the one proposed in this work. The presented work gives good results for error analysis compared to other methods and, due to its simplicity, justify its possible application