Optimização estrutural na análise não linear dos modelos de escoras e tirantes

Dissertação para obtenção do Grau de Mestre em Engenharia Civil - Perfil Estruturas

Contributo para a modelização de magnetos supercondutores de fluxo residual: aplicação a um motor linear todo supercondutor

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Re-Use Assessment of Thermoset Composite Wastes as Aggregate and Filler Replacement for Concrete-Polymer Composite Materials: A case study regarding GFRP pultrusion wastes

Glass fibre-reinforced plastics (GFRP), nowadays commonly used in the construction, transportation and automobile sectors, have been considered inherently difficult to recycle due to both the cross-linked nature of thermoset resins, which cannot be remoulded, and the complex composition of the composite itself, which includes glass fibres, polymer matrix and different types of inorganic fillers. Hence, to date, most of the thermoset based GFRP waste is being incinerated or landfilled leading to negative environmental impacts and additional costs to producers and suppliers. With an increasing awareness of environmental matters and the subsequent desire to save resources, recycling would convert an expensive waste disposal into a profitable reusable material. In this study, the effect of the incorporation of mechanically recycled GFRP pultrusion wastes on flexural and compressive behaviour of polyester polymer mortars (PM) was assessed. For this purpose, different contents of GFRP recyclates (0%, 4%, 8% and 12%, w/w), with distinct size grades (coarse fibrous mixture and fine powdered mixture), were incorporated into polyester PM as sand aggregates and filler replacements. The effect of the incorporation of a silane coupling agent was also assessed. Experimental results revealed that GFRP waste filled polymer mortars show improved mechanical behaviour over unmodified polyester based mortars, thus indicating the feasibility of GFRP waste reuse as raw material in concrete-polymer composites.

Sustainability Improvement of a composite materials’ industry through recycling and re-engineering process approaches

Recent Advances in Mechanics and Materials in Design

On the analysis of data emerging in non-linear and complex systemscomparison of two X-Ray prony spectra

New arguments proving that successive (repeated) measurements have a memory and actually remember each other are presented. The recognition of this peculiarity can change essentially the existing paradigm associated with conventional observation in behavior of different complex systems and lead towards the application of an intermediate model (IM). This IM can provide a very accurate fit of the measured data in terms of the Prony's decomposition. This decomposition, in turn, contains a small set of the fitting parameters relatively to the number of initial data points and allows comparing the measured data in cases where the “best fit” model based on some specific physical principles is absent. As an example, we consider two X-ray diffractometers (defined in paper as A- (“cheap”) and B- (“expensive”) that are used after their proper calibration for the measuring of the same substance (corundum a-Al2O3). The amplitude-frequency response (AFR) obtained in the frame of the Prony's decomposition can be used for comparison of the spectra recorded from (A) and (B) - X-ray diffractometers (XRDs) for calibration and other practical purposes. We prove also that the Fourier decomposition can be adapted to “ideal” experiment without memory while the Prony's decomposition corresponds to real measurement and can be fitted in the frame of the IM in this case. New statistical parameters describing the properties of experimental equipment (irrespective to their internal “filling”) are found. The suggested approach is rather general and can be used for calibration and comparison of different complex dynamical systems in practical purposes.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Contributo para o estudo do motor linear síncrono supercondutor

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Non-linear time series models

The last three decades have seen quite dramatic changes the way we modeled time dependent data. Linear processes have been in the center stage in modeling time series. As far as the second order properties are concerned, the theory and the methodology are very adequate.However, there are more and more evidences that linear models are not sufficiently flexible and rich enough for modeling purposes and that failure to account for non-linearities can be very misleading and have undesired consequences.

Analyzing Multiple Outcomes: Is it Really Worth the use of Multivariate Linear Regression?

In health related research it is common to have multiple outcomes of interest in a single study. These outcomes are often analysed separately, ignoring the correlation between them. One would expect that a multivariate approach would be a more efficient alternative to individual analyses of each outcome. Surprisingly, this is not always the case. In this article we discuss different settings of linear models and compare the multivariate and univariate approaches. We show that for linear regression models, the estimates of the regression parameters associated with covariates that are shared across the outcomes are the same for the multivariate and univariate models while for outcome-specific covariates the multivariate model performs better in terms of efficiency.

Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

Correlação entre a Extensão Linear do Tronco e o Alinhamento Segmentar do Membro Inferior Contralesional na Posição de Pé em Indivíduos Pós-AVE

O controlo postural (CP) do tronco é um pré-requisito para o movimento tendo como objetivo prevenir e minimizar as perturbações. Um CP adequado pressupõe estabilidade e orientação dos segmentos, sendo necessária uma orientação do tronco com componente de extensão linear para as atividades sentado e pé. Num acidente vascular encefálico (AVE), pode existir comprometimento do CP do tronco quer contralesional (CONTRA) como ipsilesional (IPSI). Neurofisiologicamente, parece haver uma projecção predominantemente ipsilateral para garantir um CP do tronco contralateralmente ao movimento, tornando-se importante perceber a correlação entre componentes do CP do tronco e o alinhamento do membro CONTRA. Contudo, atualmente são poucos os estudos direcionados para a o membro inferior (MI). Assim, uma vez que nesta população, assumir a posição de pé e realizar marcha constitui muitas vezes o seu principal objetivo, considerou-se relevante avaliar a correlação entre a extensão linear do tronco e o alinhamento segmentar do MI CONTRA na posição de pé. Participantes e Métodos: Estudo observacional, transversal, analítico com 11 indivíduos (idade média 70+10 anos, 54,5% homens). Como critérios de inclusão definiram-se AVE isquémico da artéria cerebral média, único e unilateral, em fase crónica. Recorrendo a um software de avaliação postural (SAPo) avaliou-se a extensão linear do tronco (alinhamento dos acrómios, alinhamento das espinhas ilíacas ântero-superiores (EIAS), ângulo formado entre os dois e o alinhamento vertical do tronco) e o alinhamento segmentar do MI (ângulo do joelho e ângulo entre o tronco e MI). Para a análise estatística inferencial utilizou-se o coeficiente de correlação de Pearson entre o ângulo dos acrómios e as EIAS, o alinhamento vertical do tronco e o alinhamento horizontal da pélvis IPSI com as variáveis de alinhamento do MI, para uma significância de 0,05. Resultados: Algumas correlações mostraram ser quase nulas (com valores entre -0,02 a 0,02) ou fracas como o alinhamento horizontal da pélvis IPSI com o ângulo do tronco e MI CONTRA (0,29 com p=0,39). O alinhamento do tronco e o ângulo do joelho apresentou moderada correlação (0,642), estatisticamente significativa (p=0,03). Conclusão: Os resultados deste estudo sugerem a existência de uma correlação positiva entre o alinhamento vertical do tronco e a extensão do joelho do MI CONTRA na posição de pé em indivíduos pós-AVE.

Linear amplification with multiple nonlinear devices

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e Computadores

Estudo de avaliação de emissões de nanopartículas na soldadura por fricção linear de ligas de alumínio

Dissertação para obtenção do Grau de Mestre em Engenharia Mecânica

Fluência de materiais

A presente dissertação apresenta uma abordagem ao tema Fluência, com um desenvolvimento geral para quatro materiais: madeira, alumínio, betão e aço. No entanto, particularizou-se este estudo apenas para dois destes materiais, a madeira e o alumínio. A madeira é um material viscoelástico, logo fortemente influenciado quando submetido a uma ação constante (Fluência) sendo agravada com alterações do teor em água. Iniciou-se o estudo, com uma introdução aos objetivos principais e a revisão teórica do conhecimento da propriedade mecânica (Fluência). Efetuou-se o estudo inicial para os quatro materiais indicados. Posteriormente, fez-se avaliação do efeito mecânico sortivo durante 60 dias com sete ciclos, em provetes de dimensões 20 x 20 x 400 mm3 (escala 1:10) de madeira de Eucalyptus globulus Labill. Recorrendo ao levantamento de um conjunto de modelos numéricos, procedeu-se ao ajuste e extrapolação do comportamento, em Fluência, para distintos períodos de tempo (1, 10 e 50 anos). Os resultados obtidos demonstraram que a madeira de Eucalipto não apresenta um limite no seu comportamento em Fluência, logo instável para os 60 dias de duração de ensaio. Os diferentes modelos de Fluência (x6) apresentaram uma variabilidade crescente de resultados, de acordo com o aumento de extrapolação dos resultados. Para a espécie de madeira de Eucalipto constatou-se ainda, que o ajuste e extrapolação de deformação para 50 anos ultrapassaram os valores sugeridos pelo Eurocódigo 5. A última parte deste trabalho, incidiu sobre o desenvolvimento da metodologia do ensaio em flexão de 3 provetes de alumínio similares, cujas dimensões eram de 20 x 20 x 400mm3. O objetivo desta metodologia foi avaliar o seu comportamento em Fluência. Numa primeira fase, foi aplicada uma carga contante de 160 kN. E numa segunda fase, foi aplicada o dobro dessa carga sujeita adicionalmente a uma temperatura bastante superior à temperatura ambiente (a rondar os 50 oC). Conclusivamente verificou-se que o alumínio não apresenta deformação por Fluência, para as condições de ensaio apresentadas.