918 resultados para multiscale elasticity
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The aim of this study was to evaluate the following acrylic resins: Clássico®, QC-20® and Lucitone®, recommended specifically for thermal polymerization, and Acron MC® and VIPI-WAVE®, made for polymerization by microwave energy. The resins were evaluated regarding their surface nanohardness and modulus of elasticity, while varying the polymerization time recommended by the manufacturer. They were also compared as to the presence of water absorbed by the samples. The technique used was nanoindentation, using the Nano Indenter XP®, MTS. According to an intra-group analysis, when using the polymerization time recommended by the manufacturer, a variation of 0.14 to 0.23 GPa for nanohardness and 2.61 to 3.73 GPa for modulus of elasticity was observed for the thermally polymerized resins. The variation for the resins made for polymerization by microwave energy was 0.15 to 0.22 GPa for nanohardness and 2.94 to 3.73 GPa for modulus of elasticity. The conclusion was that the Classico® resin presented higher nanohardness and higher modulus of elasticity values when compared to those of the same group, while Acron MC® presented the highest values for the same characteristics when compared to those of the same group. The water absorption evaluation showed that all the thermal polymerization resins, except for Lucitone®, presented significant nanohardness differences when submitted to dehydration or rehydration, while only Acron MC® presented no significant differences when submitted to a double polymerization time. Regarding the modulus of elasticity, it was observed that all the tested materials and products, except for Lucitone®, showed a significant increase in modulus of elasticity when submitted to a lack of hydration.
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There is a considerable debate about the potential influence of fetal programming on cardiovascular diseases in adulthood. In the present prospective epidemiological cohort study, the relationship between birthweight and arterial elasticity in 472 children between 5 and 8 years of age was assessed. LAEI (large artery elasticity index), SAEI (small artery elasticity index) and BP (blood pressure) were assessed using the HDI/PulseWave CR-2000 CardioVascular Profiling System. Blood concentrations of glucose, total cholesterol and its fractions [LDL (low-density lipoprotein)-cholesterol and HDL (high-density lipoprotein)-cholesterol] and triacylglycerols (triglycerides) were determined by automated enzymatic methods. Insulin was assessed by a chemiluminescent method, insulin resistance by HOMA (homoeostasis model assessment) and CRP (C-reactive protein) by immunonephelometry. Two linear regression models were applied to investigate the relationship between the outcomes, LAEI and SAEI, and the following variables: birthweight, gestational age, glucose, LDL-cholesterol, HDL-cholesterol, triacylglycerols, insulin, CRP, HOMA, age, gender, waist circumference, per capita income, SBP (systolic BP) and DBP (diastolic BP). LAEI was positively associated with birthweight (P=0.036), waist circumference (P<0.001) and age (P<0.001), and negatively associated with CRP (P=0.024) and SBP (P<0.001). SAEI was positively associated with birthweight (P=0.04), waist circumference (P=0.001) and age (P<0.001), and negatively associated with DBP (P<0.001). Arterial elasticity was decreased in apparently healthy children who had lower birthweights, indicating an earlier atherogenetic susceptibility to cardiovascular diseases in adolescence and adult life. Possible explanations for the results include changes in angiogenesis during critical phases of intrauterine life caused by periods of fetal growth inhibition and local haemodynamic anomalies
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This work is related to the so-called non-conventional finite element formulations. Essentially, a methodology for the enrichment of the initial approximation which is typical of the meshless methods and based on the clouds concept is introduced in the hybrid-Trefftz formulation for plane elasticity. The formulation presented allows for the approximation and direct enrichment of two independent fields: stresses in the domains and displacements on the boundaries of the elements. Defined by a set of elements and interior boundaries sharing a common node, the cloud notion is employed to select the enrichment support for the approximation fields. The numerical analysis performed reveals an excellent performance of the resulting formulation, characterized by the good approximation ability and a reduced computational effort. Copyright (C) 2009 John Wiley & Sons, Ltd.
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We consider a class of two-dimensional problems in classical linear elasticity for which material overlapping occurs in the absence of singularities. Of course, material overlapping is not physically realistic, and one possible way to prevent it uses a constrained minimization theory. In this theory, a minimization problem consists of minimizing the total potential energy of a linear elastic body subject to the constraint that the deformation field must be locally invertible. Here, we use an interior and an exterior penalty formulation of the minimization problem together with both a standard finite element method and classical nonlinear programming techniques to compute the minimizers. We compare both formulations by solving a plane problem numerically in the context of the constrained minimization theory. The problem has a closed-form solution, which is used to validate the numerical results. This solution is regular everywhere, including the boundary. In particular, we show numerical results which indicate that, for a fixed finite element mesh, the sequences of numerical solutions obtained with both the interior and the exterior penalty formulations converge to the same limit function as the penalization is enforced. This limit function yields an approximate deformation field to the plane problem that is locally invertible at all points in the domain. As the mesh is refined, this field converges to the exact solution of the plane problem.
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A macrodynamic model is proposed in which the real exchange rate and the elasticity of labour supply interact defining different trajectories of growth and income distribution in a developing economy. Growth depends on imports of capital goods which are paid with exports (there are no capital flows) and hence is constrained by equilibrium in current account. The role of the elasticity of labour supply is to prevent the real exchange rate from appreciating as the economy grows, thereby sustaining international competitiveness. The model allows for endogenous technological change and considers the impact of migration from the subsistence to the modern sector on the cumulative (Kaldor-Verdoorn) process of learning.
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Different stoichiometries are observed between alpha and beta subunits of Na,K-ATPase that depend on the method employed to solubilize and purify the enzyme. It is not known whether this variability is due to loss of protein-protein association, or is a result of the replacement of essential phospholipids by detergent molecules. With the aim of understanding the effect of enzyme/surfactant ratio on both the catalytic activity and the enzyme structure, we have investigated the bulk and surface properties of the enzyme. The circular dichroism (CD) spectra, surface tension and dilatational surface elasticity results were compared with the residual ATPase activity of the Na,K-ATPase in different surfactant and protein concentrations. Na,K-ATPase in the (alpha beta)(2) form dissociated to the alpha beta form on dilution, and associated to the (alpha beta)(4) form when concentrated. These different stoichiometries have similar ATPase activities and are in equilibrium at C(12)E(8) concentrations below the CIVIC (0.053 mg mL(-1)). At detergent concentrations above the CIVIC the ATPase activity of all forms was abolished, which is concomitant with the dissociation of the a and subunits. (C) 2008 Elsevier Inc. All rights reserved.
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Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.
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The positioning of the consumers in the power systems operation has been changed in the recent years, namely due to the implementation of competitive electricity markets. Demand response is an opportunity for the consumers’ participation in electricity markets. Smart grids can give an important support for the integration of demand response. The methodology proposed in the present paper aims to create an improved demand response program definition and remuneration scheme for aggregated resources. The consumers are aggregated in a certain number of clusters, each one corresponding to a distinct demand response program, according to the economic impact of the resulting remuneration tariff. The knowledge about the consumers is obtained from its demand price elasticity values. The illustrative case study included in the paper is based on a 218 consumers’ scenario.
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
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Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos
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This paper analyses the elasticities of demand in tolled motorways in Spain with respect to the main variables influencing it. The demand equation is estimated using a panel data set where the cross-section observations correspond to the different Spanish tolled motorways sections, and the temporal dimension ranges from the beginning of the eighties until the end of the nineties. The results show a high elasticity with respect to the economic activity level. The average elasticity with respect to petrol price falls around -0.3, while toll elasticities clearly vary across motorway sections. These motorway sections are classified into four groups according to the estimated toll elasticity with values that range from -0.21 for the most inelastic to -0.83 for the most elastic. The main factors that explain such differences are the quality of the alternative road and the length of the section. The long-term effect is about 50 per cent higher than the short term one; however, the period of adjustment is relatively short.
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In this paper we check whether generator's bid behavior at the Spanish whosale electricity market is consistent with the hypothesis of profit maximization on their residual demands. Using OMEL data, we find the arc-elacticity of the residual demand around the system marginal price. The results suggest thet the larger firms are not actually profit-msximization. We argue how the regulatory environment may drive these results. Finally, we repeat the analysis for the first session of the intra-day market where presumably firms may not have the same incentives as in the day-ahead market.
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This paper presents a semisupervised support vector machine (SVM) that integrates the information of both labeled and unlabeled pixels efficiently. Method's performance is illustrated in the relevant problem of very high resolution image classification of urban areas. The SVM is trained with the linear combination of two kernels: a base kernel working only with labeled examples is deformed by a likelihood kernel encoding similarities between labeled and unlabeled examples. Results obtained on very high resolution (VHR) multispectral and hyperspectral images show the relevance of the method in the context of urban image classification. Also, its simplicity and the few parameters involved make the method versatile and workable by unexperienced users.