Estudo da resistência de juntas adesivas em L entre alumínio e material compósito

As ligações adesivas são frequentemente utilizadas na fabricação de estruturas complexas que não poderiam ou não seriam tão fáceis de ser fabricadas numa só peça, a fim de proporcionar uma união estrutural que, teoricamente, deve ser pelo menos tão resistente como o material de base. As juntas adesivas têm vindo a substituir métodos como a soldadura, e ligações parafusadas e rebitadas, devido à facilidade de fabricação, menor custo, facilidade em unir materiais diferentes, melhor resistência, entre outras características. Os materiais compósitos reforçados com fibra de carbono são amplamente utilizados em muitas indústrias, tais como de construção de barcos, automóvel e aeronáutica, sendo usados em estruturas que requerem elevada resistência e rigidez específicas, o que reduz o peso dos componentes, mantendo a resistência e rigidez necessárias para suportar as diversas cargas aplicadas. Embora estes métodos de fabricação reduzam ao máximo as ligações através de técnicas de fabrico avançadas, estas ainda são necessárias devido ao tamanho dos componentes, limitações de projecto tecnológicas e logísticas. Em muitas estruturas, a combinação de compósitos com metais tais como alumínio ou titânio traz vantagens de projecto. Este trabalho tem como objectivo estudar, experimentalmente e por modelos de dano coesivo (MDC), juntas adesivas em L entre componentes de alumínio e compósito de carbono epóxido quando solicitados a forças de arrancamento, considerando diferentes configurações de junta e adesivos de ductilidade distinta. Os parâmetros geométricos abordados são a espessura do aderente de alumínio (tP2) e comprimento de sobreposição (LO). A análise numérica permitiu o estudo da distribuição das tensões, evolução do dano, resistência e modos de rotura. Os testes experimentais validam os resultados numéricos e fornecem mecanismos de projecto para juntas em L. Foi mostrado que a geometria do aderente em L (alumínio) e o tipo de adesivo têm uma influência directa na resistência de junta.

Architecture to Support Quality of Service in Arrowhead Systems

Presented at INForum - Simpósio de Informática (INFORUM 2015). 7 to 8, Sep, 2015. Covilhã, Portugal.

Real-Time Support in the Proposal for Fine-Grained Parallelism in Ada

Presented at Work in Progress Session, IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 3, Dec, 2015. San Antonio, U.S.A..

Real-Time Support in the Proposal for Fine-Grained Parallelism in Ada

Presented at Work in Progress Session, IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 3, Dec, 2015. San Antonio, U.S.A..

A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

Six thinking hats: A novel metalearner for intelligent decision support in electricity markets

The energy sector has suffered a significant restructuring that has increased the complexity in electricity market players' interactions. The complexity that these changes brought requires the creation of decision support tools to facilitate the study and understanding of these markets. The Multiagent Simulator of Competitive Electricity Markets (MASCEM) arose in this context, providing a simulation framework for deregulated electricity markets. The Adaptive Learning strategic Bidding System (ALBidS) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM, ALBidS considers several different strategic methodologies based on highly distinct approaches. Six Thinking Hats (STH) is a powerful technique used to look at decisions from different perspectives, forcing the thinker to move outside its usual way of thinking. This paper aims to complement the ALBidS strategies by combining them and taking advantage of their different perspectives through the use of the STH group decision technique. The combination of ALBidS' strategies is performed through the application of a genetic algorithm, resulting in an evolutionary learning approach.

Impact of sensor nodes scaling and velocity on handover mechanisms for healthcare wireless sensor networks with mobility support

Health promotion in hospital environments can be improved using the most recent information and communication technologies. The Internet connectivity to small sensor nodes carried by patients allows remote access to their bio-signals. To promote these features the healthcare wireless sensor networks (HWSN) are used. In these networks mobility support is a key issue in order to keep patients under realtime monitoring even when they move around. To keep sensors connected to the network, they should change their access points of attachment when patients move to a new coverage area along an infirmary. This process, called handover, is responsible for continuous network connectivity to the sensors. This paper presents a detailed performance evaluation study considering three handover mechanisms for healthcare scenarios (Hand4MAC, RSSI-based, and Backbone-based). The study was performed by simulation using several scenarios with different number of sensors and different moving velocities of sensor nodes. The results show that Hand4MAC is the best solution to guarantee almost continuous connectivity to sensor nodes with less energy consumption.

A música como expressão e cognição: a propositósito do conceito de "crítica imanente do material" em adorno

Numa recensão às conferências sobre "Metafísica - Conceitos e Problemas" {Metaphysik. Begriffe und Probleme), proferidas por Adorno, na Universidade de Frankfurt, no segundo semestre de 1965 e publicadas postumamente, o filósofo dinamarquês Stâle R. S. Finke (1999) analisa os "esforços" de Adorno por "recuperar a concepção da experiência metafísica". Uma tal recuperação teria de ser compreendida num quadro de pensamento que é o da "dialéctica negativa", por sua vez tributária dos padrões kantianos de "consciência conceptual e autonomia moral" que Adorno articula naquilo a que Finke chama o "projecto" ou o "ideal de liberdade expressiva". O conceito de experiência metafísica, formulado nas referidas conferências, seria, assim, da maior importância para Adorno, pois que nele se daria expressão ao objectivo da "dialéctica negativa" (a Negative Dialektik foi publicada no ano seguinte, 1966): "a invocação do não-idêntico como condição de experiência e de expressão". "Relacionada intrinsecamente" com o "donnnio da experiência possível", histórica e cultural, isto é, com tudo aquilo que constrange a autonomia (por um lado permitindo, por outro lado limitando as possibilidades do eu), a concepção da experiência metafísica em Adorno convoca essas possibilidades do eu como inalcançadas

Monitoring morphisms to support sustainable interoperability of enterprise systems

Dissertation to obtain the Master degree in Electrical Engineering and Computer Science

Ankle antagonist coactivation in the double-support phase of walking: Stroke vs. healthy subjects

Introduction: Lesions at ipsilateral systems related to postural control at ipsilesional side, may justify the lower performance of stroke subjects during walking. Purpose: To analyse bilateral ankle antagonist coactivation during double-support in stroke subjects. Methods: Sixteen (8 females; 8 males) subjects with a first isquemic stroke, and twenty two controls (12 females; 10 males) participated in this study. The double support phase was assessed through ground reaction forces and electromyography of ankle muscles was assessed in both limbs. Results: Ipsilesional limb presented statistical significant differences from control when assuming specific roles during double support, being the tibialis anterior and soleus pair the one in which this atypical behavior was more pronounced. Conclusion: The ipsilesional limb presents a dysfunctional behavior when a higher postural control activity was demanded.

Cross-Layer Admission Control to Enhance the Support of Real-Time Applications in WSN

Real-time monitoring applications may be used in a wireless sensor network (WSN) and may generate packet flows with strict quality of service requirements in terms of delay, jitter, or packet loss. When strict delays are imposed from source to destination, the packets must be delivered at the destination within an end-to-end delay (EED) hard limit in order to be considered useful. Since the WSN nodes are scarce both in processing and energy resources, it is desirable that they only transport useful data, as this contributes to enhance the overall network performance and to improve energy efficiency. In this paper, we propose a novel cross-layer admission control (CLAC) mechanism to enhance the network performance and increase energy efficiency of a WSN, by avoiding the transmission of potentially useless packets. The CLAC mechanism uses an estimation technique to preview packets EED, and decides to forward a packet only if it is expected to meet the EED deadline defined by the application, dropping it otherwise. The results obtained show that CLAC enhances the network performance by increasing the useful packet delivery ratio in high network loads and improves the energy efficiency in every network load.

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.

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.

Estudo da antiga mina de volfrâmio das Aveleiras (Mire de Tibães): cartografia geotécnica e avaliação geomecânica

Este trabalho tem como objetivo sublinhar a importância de um estudo geológico‐geotécnico para apoiar a cartografia geotécnica do maciço rochoso subterrâneo da antiga mina de volfrâmio das Aveleiras (Mosteiro de Tibães, Braga). Foi realizado um trabalho de campo sistemático, ao longo de uma rede de galerias subterrâneas com uma extensão aproximada de 155 m. Estas galerias são constituídas, principalmente, por rochas metassedimentares, embora aflorem rochas graníticas num pequeno trecho de uma das galerias. A técnica de amostragem linear de descontinuidades aplicada ao grau de compartimentação do maciço rochoso esteve na base de todos os dados geológicos, geotécnicos e geomecânicos. Além disso, foram coligidos e integrados os dados de campanhas de campo anteriores, realizadas entre 2006 e 2011. Foram igualmente descritos os métodos de avaliação dos dados de campo, bem como a análise estatística dos parâmetros geológico‐geotécnicos. O zonamento geotécnico do maciço rochoso das Aveleiras foi desenvolvido tendo em conta o comportamento do maciço rochoso in situ, e foi apoiado por ensaios laboratoriais de resistência do material‐rocha através do Ensaio de Carga Pontual. Apresenta‐se uma proposta preliminar de zonamento geomecânico com o objectivo de apoiar o projeto de engenharia de maciços rochosos.