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No description available.

Unsteady large-scale vortices, formed by the roll-up of free shear layers separating along sharp edges, are the dominant flow characteristics of the turbulent flow over buildings. These vortical structures interact with each other and with the building surface resulting in secondary separation and severe pressure fluctuations. Moreover, the interaction of the large-scale vortices with the multiplicity of turbulence scales in the incoming wind exacerbates their unsteady motion and hence significantly affects the pressure fluctuations spectra experienced by the building. Large-eddy simulations are conducted to study the interaction of homogeneous turbulence in the incident flow with a surface-mounted prism. A compact fifth-order upwind difference scheme is used to effectively and accurately perform the simulations. Three cases of incident flow are considered. In one case, the prism is placed in a smooth uniform flow. In the second case, homogeneous isotropic turbulence with von Karman spectrum is superimposed on the uniform flow at the inflow boundary. The integral length scale is one-half the prism height. In the third case, the integral length scale is equal to the prism height. The numerical results are compared with experimental measurements reported by Tieleman et al. (2002). The results show that the highest negative mean value of the pressure coefficient on the roof and the sides is about 30% larger in case two of turbulent inflow and takes place closer to the windward edge of the prism. Moreover, the pressure coefficients on the roof and sides of the prism in the case of turbulent inflow show a higher level of variations in comparison with the case of smooth inflow conditions. The predicted mean characteristics of the pressure coefficients in the turbulent case match the experimental values in terms of both magnitude and location on the roof of the prism reported in Tieleman et al. (1998) and Tieleman et al. (2002). As for the peak value, the peak value of -2 obtained in the turbulent inflow case two is about 20% smaller than the values measured experimentally by Tieleman et al. (2002). On the other hand, it is stressed that the peak value in the simulations would increase as the duration of the simulation is increased to match that of the experimental measurement. The results also show that the turbulent case yields a non-exceedence probability for the peak pressure coefficient that is closer to the one obtained from the measured data than the smooth case data. Also, spectral and cross-spectral analysis are carried out using complex Morlet wavelet transform to investigate pressure-velocity relation. The study shows that the nonlinearity in the relationship of velocity-pressure is detected using wavelet bicoherence. / Ph. D.

Regression Wavelet Analysis (RWA) is a novel wavelet-based scheme for coding hyperspectral images that employs multiple regression analysis to exploit the relationships among spectral wavelet transformed components. The scheme is based on a pyramidal prediction, using different regression models, to increase the statistical independence in the wavelet domain For lossless coding, RWA has proven to be superior to other spectral transform like PCA and to the best and most recent coding standard in remote sensing, CCSDS-123.0. In this paper we show that RWA also allows progressive lossy-to-lossless (PLL) coding and that it attains a rate-distortion performance superior to those obtained with state-of-the-art schemes. To take into account the predictive significance of the spectral components, we propose a Prediction Weighting scheme for JPEG2000 that captures the contribution of each transformed component to the prediction process.

The identification of energy scales in the region of Isoscalar Giant Quadrupole Resonance (ISGQR) is motivated by their potential use in understanding how an ordered collective motion transforms into a disordered motion of intrinsic single-particle degrees-of-freedom in many-body quantum systems. High energy-resolution measurements of the ISGQR were obtained by proton inelastic scattering at Ep= 200 MeV using the K600 magnetic Spectrometer at iThemba LABS. The nuclei 58Ni, 90Zr, 120Sn and 208Pb, associated with closed shells, were investigated. Both the Fourier transform and Wavelet analysis were used to extract characteristic energy scales and were later compared with the results from the theoretical microscopic Quasi-particle Phonon Model (QPM), including contributions from collective and non-collective states. The scales found in the experimental data were in good agreement with the QPM. This provides a strong argument that the observed energy scales result from the decay of the collective modes into 2p-2h states. The different scale regions were tested directly by reconstruction of measured energy spectra using the Inverse Fourier Transform and the Continuous Wavelet Transform (CWT), together with a comparison to a previously available reconstruction using the Discrete Wavelet Transform (DWT).

A crescente utilização de novas tecnologias, as quais necessitam de uma fonte de energia menor e mais eficiente, como os microssensores para monitoramento de sistemas e estruturas nas chamadas cidades inteligentes, torna a captura da energia do ambiente uma opção viável para alimentação de tais dispositivos. Como a energia cinética é uma fonte de energia facilmente encontrada no ambiente, os sistemas que a capturam e convertem em eletricidade têm sido amplamente estudados, especialmente os que utilizam transdutores piezoelétricos. Considerando estruturas aporticadas, como prédios, pontes etc., comumente encontradas nas cidades, este trabalho apresenta um novo modelo de sistema de captura de energia piezoelétrico com base em um pórtico não linear, sob uma excitação não ideal, por meio de uma fonte com potência limitada. Para modelar o acoplamento piezoelétrico, foram consideradas as não linearidades do material piezoelétrico. Por meio das simulações numéricas, pode-se verificar a eficiência e a viabilidade do modelo proposto. Devido ao fato de as vibrações do meio ambiente serem senoidais, aleatórias ou transitórias, surge uma dificuldade na captura de energia de forma eficiente e com um nível contínuo. A utilização de controles passivos pode melhorar a energia capturada, removendo o movimento caótico do sistema e mantendo a oscilação em uma órbita periódica estável. Assim, duas estratégias de controle passivo foram empregadas, a primeira utilizando uma subestrutura com características de absorvedor de energia não linear (NES) e a segunda pela introdução de um pêndulo. Em ambos os casos, as simulações demonstraram que o controle passivo foi eficiente em levar o sistema caótico para uma órbita periódica estável, otimizando a captura de energia do sistema. Uma análise considerando incertezas nos parâmetros foi realizada, para verificar a robustez da estratégia de controle, assim como a sensibilidade do sistema de controle a erros paramétricos. Os resultados mostraram a eficiência do controle passivo e o fenômeno do bombeamento de energia na supressão do comportamento caótico. A principal vantagem do controle passivo é não necessitar de componentes eletrônicos para controlar o sistema, sendo apenas um componente mecânico \"massa\", acoplado à estrutura principal. Uma análise wavelet foi realizada sobre o modelo, para identificar o comportamento oscilatório do sistema e permitir a visualização das frequências de vibração que capturam mais energia. / The increasing use of new technologies, which have the need for smaller and more energy efficient sources, such as micro-sensors for monitoring systems and structures of the so-called smart cities, assigns environmental energy harvesting a viable option to power such devices. As kinetic energy is a source easily found in the environment, the systems that harvest and convert this type of energy into electricity have been widely studied, especially those using piezoelectric transducers. Considering framed structures, such as buildings, bridges, etc., which are commonly found in the cities, this paper presents a new model of piezoelectric energy harvesting system based on a nonlinear portal frame, under a non-ideal excitation by a source with limited power. To model Piezoelectric couplings, they were considered nonlinearities of the piezoelectric material. Through numerical simulations, the effciency and viability of the proposed model can be verified. A difficulty arises in harvesting energy in an efficient manner, and with a continuous level, because the vibrations of the environment are sinusoidal, random or transient. However, the use of passive controls can improve the energy harvested by removing the chaotic motion of the system and maintaining the oscillation at a stable periodic orbit. Thus, two passive control strategies were employed, the first using a substructure with characteristics of nonlinear energy sink (NES), and the second by introducing a pendulum. In both cases, the simulations showed that the passive control was efficient in bringing the chaotic system to a stable periodic orbit, optimizing the energy harvest system. An analysis considering the uncertainties in the parameters was performed to verify the robustness of the control strategy, as well as the sensitivity of the control system of parametric errors. The results showed the efficiency of passive control and the energy pumping phenomenon in the suppression of the chaotic behavior. The main advantage of passive control is not to require any electronic components for controlling the system, only a mechanical component _mass_, attached to the main structure. A Wavelet Analysis was conducted on the model to identify the oscillatory behavior of the system and allowed the viewing of the vibration frequencies that harvest more energy.

Financialization of crude oil and its frequent inclusion into investment portfo- lios raise the demand for proper correlation estimates of this commodity and other financial assets. This thesis particularly examines the co-movement of crude oil price with prices of four other representatives of commodity market (gasoline, natural gas, gold and Industrials Index). It contributes to the exist- ing literature by the results obtained from application of wavelet coherence, which allows uncovering dynamics of interconnection between commodity prices in time as well as over different frequencies. Analysis brings many in- teresting findings and practical implications. Among others, it specifies the investment horizons that should be considered to maximize diversification properties of studied commodities. 1

A crescente utilização de novas tecnologias, as quais necessitam de uma fonte de energia menor e mais eficiente, como os microssensores para monitoramento de sistemas e estruturas nas chamadas cidades inteligentes, torna a captura da energia do ambiente uma opção viável para alimentação de tais dispositivos. Como a energia cinética é uma fonte de energia facilmente encontrada no ambiente, os sistemas que a capturam e convertem em eletricidade têm sido amplamente estudados, especialmente os que utilizam transdutores piezoelétricos. Considerando estruturas aporticadas, como prédios, pontes etc., comumente encontradas nas cidades, este trabalho apresenta um novo modelo de sistema de captura de energia piezoelétrico com base em um pórtico não linear, sob uma excitação não ideal, por meio de uma fonte com potência limitada. Para modelar o acoplamento piezoelétrico, foram consideradas as não linearidades do material piezoelétrico. Por meio das simulações numéricas, pode-se verificar a eficiência e a viabilidade do modelo proposto. Devido ao fato de as vibrações do meio ambiente serem senoidais, aleatórias ou transitórias, surge uma dificuldade na captura de energia de forma eficiente e com um nível contínuo. A utilização de controles passivos pode melhorar a energia capturada, removendo o movimento caótico do sistema e mantendo a oscilação em uma órbita periódica estável. Assim, duas estratégias de controle passivo foram empregadas, a primeira utilizando uma subestrutura com características de absorvedor de energia não linear (NES) e a segunda pela introdução de um pêndulo. Em ambos os casos, as simulações demonstraram que o controle passivo foi eficiente em levar o sistema caótico para uma órbita periódica estável, otimizando a captura de energia do sistema. Uma análise considerando incertezas nos parâmetros foi realizada, para verificar a robustez da estratégia de controle, assim como a sensibilidade do sistema de controle a erros paramétricos. Os resultados mostraram a eficiência do controle passivo e o fenômeno do bombeamento de energia na supressão do comportamento caótico. A principal vantagem do controle passivo é não necessitar de componentes eletrônicos para controlar o sistema, sendo apenas um componente mecânico \"massa\", acoplado à estrutura principal. Uma análise wavelet foi realizada sobre o modelo, para identificar o comportamento oscilatório do sistema e permitir a visualização das frequências de vibração que capturam mais energia. / The increasing use of new technologies, which have the need for smaller and more energy efficient sources, such as micro-sensors for monitoring systems and structures of the so-called smart cities, assigns environmental energy harvesting a viable option to power such devices. As kinetic energy is a source easily found in the environment, the systems that harvest and convert this type of energy into electricity have been widely studied, especially those using piezoelectric transducers. Considering framed structures, such as buildings, bridges, etc., which are commonly found in the cities, this paper presents a new model of piezoelectric energy harvesting system based on a nonlinear portal frame, under a non-ideal excitation by a source with limited power. To model Piezoelectric couplings, they were considered nonlinearities of the piezoelectric material. Through numerical simulations, the effciency and viability of the proposed model can be verified. A difficulty arises in harvesting energy in an efficient manner, and with a continuous level, because the vibrations of the environment are sinusoidal, random or transient. However, the use of passive controls can improve the energy harvested by removing the chaotic motion of the system and maintaining the oscillation at a stable periodic orbit. Thus, two passive control strategies were employed, the first using a substructure with characteristics of nonlinear energy sink (NES), and the second by introducing a pendulum. In both cases, the simulations showed that the passive control was efficient in bringing the chaotic system to a stable periodic orbit, optimizing the energy harvest system. An analysis considering the uncertainties in the parameters was performed to verify the robustness of the control strategy, as well as the sensitivity of the control system of parametric errors. The results showed the efficiency of passive control and the energy pumping phenomenon in the suppression of the chaotic behavior. The main advantage of passive control is not to require any electronic components for controlling the system, only a mechanical component _mass_, attached to the main structure. A Wavelet Analysis was conducted on the model to identify the oscillatory behavior of the system and allowed the viewing of the vibration frequencies that harvest more energy.

Large-scale mining practices have disturbed many natural watersheds in northern Alberta, Canada. To restore disturbed landscapes and ecosystems functions, reconstruction strategies have been adopted with the aim of establishing sustainable reclaimed lands. The success of the reconstruction process depends on the design of reconstruction strategies, which can be optimized by improving the understanding of the controlling hydrological processes in the reconstructed watersheds. Evapotranspiration is one of the important components of the hydrological cycle; its estimation and analysis are crucial for better assessment of the reconstructed landscape hydrology, and for more efficient design. The complexity of the evapotranspiration process and its variability in time and space has imposed some limitations on previously developed evapotranspiration estimation models. The vast majority of the available models estimate the rate of potential evapotranspiration, which occurs under unlimited water supply condition. However, the rate of actual evapotranspiration (AET) depends on the available soil moisture, which makes its physical modeling more complicated than the potential evapotranspiration. The main objective of this study is to estimate and analyze the AET process in a reconstructed landscape.<p> Data driven techniques can model the process without having a complete understanding of its physics. In this study, three data driven models; genetic programming (GP), artificial neural networks (ANNs), and multilinear regression (MLR), were developed and compared for estimating the hourly eddy covariance (EC)-measured AET using meteorological variables. The AET was modeled as a function of five meteorological variables: net radiation (Rn), ground temperature (Tg), air temperature (Ta), relative humidity (RH), and wind speed (Ws) in a reconstructed landscape located in northern Alberta, Canada. Several ANN models were evaluated using two training algorithms of Levenberg-Marquardt and Bayesian regularization. The GP technique was employed to generate mathematical equations correlating AET to the five meteorological variables. Furthermore, the available data were statistically analyzed to obtain MLR models and to identify the meteorological variables that have significant effect on the evapotranspiration process. The utility of the investigated data driven models was also compared with that of HYDRUS-1D model, which is a physically based model that makes use of conventional Penman-Monteith (PM) method for the prediction of AET. HYDRUS-1D model was examined for estimating AET using meteorological variables, leaf area index, and soil moisture information. Furthermore, Wavelet analysis (WA), as a multiresolution signal processing tool, was examined to improve the understanding of the available time series temporal variations, through identifying the significant cyclic features, and to explore the possible correlation between AET and the meteorological signals. WA was used with the purpose of input determination of AET models, a priori.<p> The results of this study indicated that all three proposed data driven models were able to approximate the AET reasonably well; however, GP and MLR models had better generalization ability than the ANN model. GP models demonstrated that the complex process of hourly AET can be efficiently modeled as simple semi-linear functions of few meteorological variables. The results of HYDRUS-1D model exhibited that a physically based model, such as HYDRUS-1D, might perform on par or even inferior to the data driven models in terms of the overall prediction accuracy. The developed equation-based models; GP and MLR, revealed the larger contribution of net radiation and ground temperature, compared to other variables, to the estimation of AET. It was also found that the interaction effects of meteorological variables are important for the AET modeling. The results of wavelet analysis demonstrated the presence of both small-scale (2 to 8 hours) and larger-scale (e.g. diurnal) cyclic features in most of the investigated time series. Larger-scale cyclic features were found to be the dominant source of temporal variations in the AET and most of the meteorological variables. The results of cross wavelet analysis indicated that the cause and effect relationship between AET and the meteorological variables might vary based on the time-scale of variation under consideration. At small time-scales, significant linear correlations were observed between AET and Rn, RH, and Ws time series, while at larger time-scales significant linear correlations were observed between AET and Rn, RH, Tg, and Ta time series.

Large-scale mining practices have disturbed many natural watersheds in northern Alberta, Canada. To restore disturbed landscapes and ecosystems functions, reconstruction strategies have been adopted with the aim of establishing sustainable reclaimed lands. The success of the reconstruction process depends on the design of reconstruction strategies, which can be optimized by improving the understanding of the controlling hydrological processes in the reconstructed watersheds. Evapotranspiration is one of the important components of the hydrological cycle; its estimation and analysis are crucial for better assessment of the reconstructed landscape hydrology, and for more efficient design. The complexity of the evapotranspiration process and its variability in time and space has imposed some limitations on previously developed evapotranspiration estimation models. The vast majority of the available models estimate the rate of potential evapotranspiration, which occurs under unlimited water supply condition. However, the rate of actual evapotranspiration (AET) depends on the available soil moisture, which makes its physical modeling more complicated than the potential evapotranspiration. The main objective of this study is to estimate and analyze the AET process in a reconstructed landscape.<p> Data driven techniques can model the process without having a complete understanding of its physics. In this study, three data driven models; genetic programming (GP), artificial neural networks (ANNs), and multilinear regression (MLR), were developed and compared for estimating the hourly eddy covariance (EC)-measured AET using meteorological variables. The AET was modeled as a function of five meteorological variables: net radiation (Rn), ground temperature (Tg), air temperature (Ta), relative humidity (RH), and wind speed (Ws) in a reconstructed landscape located in northern Alberta, Canada. Several ANN models were evaluated using two training algorithms of Levenberg-Marquardt and Bayesian regularization. The GP technique was employed to generate mathematical equations correlating AET to the five meteorological variables. Furthermore, the available data were statistically analyzed to obtain MLR models and to identify the meteorological variables that have significant effect on the evapotranspiration process. The utility of the investigated data driven models was also compared with that of HYDRUS-1D model, which is a physically based model that makes use of conventional Penman-Monteith (PM) method for the prediction of AET. HYDRUS-1D model was examined for estimating AET using meteorological variables, leaf area index, and soil moisture information. Furthermore, Wavelet analysis (WA), as a multiresolution signal processing tool, was examined to improve the understanding of the available time series temporal variations, through identifying the significant cyclic features, and to explore the possible correlation between AET and the meteorological signals. WA was used with the purpose of input determination of AET models, a priori.<p> The results of this study indicated that all three proposed data driven models were able to approximate the AET reasonably well; however, GP and MLR models had better generalization ability than the ANN model. GP models demonstrated that the complex process of hourly AET can be efficiently modeled as simple semi-linear functions of few meteorological variables. The results of HYDRUS-1D model exhibited that a physically based model, such as HYDRUS-1D, might perform on par or even inferior to the data driven models in terms of the overall prediction accuracy. The developed equation-based models; GP and MLR, revealed the larger contribution of net radiation and ground temperature, compared to other variables, to the estimation of AET. It was also found that the interaction effects of meteorological variables are important for the AET modeling. The results of wavelet analysis demonstrated the presence of both small-scale (2 to 8 hours) and larger-scale (e.g. diurnal) cyclic features in most of the investigated time series. Larger-scale cyclic features were found to be the dominant source of temporal variations in the AET and most of the meteorological variables. The results of cross wavelet analysis indicated that the cause and effect relationship between AET and the meteorological variables might vary based on the time-scale of variation under consideration. At small time-scales, significant linear correlations were observed between AET and Rn, RH, and Ws time series, while at larger time-scales significant linear correlations were observed between AET and Rn, RH, Tg, and Ta time series.