Adhesive thickness effects of a ductile adhesive by optical measurement techniques

Adhesive bonding is an excellent alternative to traditional joining techniques such as welding, mechanical fastening or riveting. However, there are many factors that have to be accounted for during joint design to accurately predict the joint strength. One of these is the adhesive layer thickness (tA). Most of the results are for epoxy structural adhesives, tailored to perform best with small values of tA, and these show that the lap joint strength decreases with increase of tA (the optimum joint strength is usually obtained with tA values between 0.1 and 0.2 mm). Recently, polyurethane adhesives were made available in the market, designed to perform with larger tA values, and whose fracture behaviour is still not studied. In this work, the effect of tA on the tensile fracture toughness (View the MathML source) of a bonded joint is studied, considering a novel high strength and ductile polyurethane adhesive for the automotive industry. This work consists on the fracture characterization of the bond by a conventional and the J-integral techniques, which accurately account for root rotation effects. An optical measurement method is used for the evaluation of crack tip opening (δn) and adherends rotation at the crack tip (θo) during the test, supported by a Matlab® sub-routine for the automated extraction of these parameters. As output of this work, fracture data is provided in traction for the selected adhesive, enabling the subsequent strength prediction of bonded joints.

Technology for creativity and innovation: tools, techniques and applications

It is widely accepted that organizations and individuals must be innovative and continually create new knowledge and ideas to deal with rapid change. Innovation plays an important role in not only the development of new business, process and products, but also in competitiveness and success of any organization. Technology for Creativity and Innovation: Tools, Techniques and Applications provides empirical research findings and best practices on creativity and innovation in business, organizational, and social environments. It is written for educators, academics and professionals who want to improve their understanding of creativity and innovation as well as the role technology has in shaping this discipline.

O empreendedorismo como fator dinamizador da competitividade regional: o papel do financiamento

Dissertação de Mestrado em Finanças Empresariais

Finanças comportamentais: sobre-reação e sub-reação no mercado bolsista português

Dissertação para obtenção do Grau de Mestre em Contabilidade e Finanças Orientador: Mestre Luis Pereira Gomes

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Data mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

Natural gas system operation: lagrangean optimization techniques

To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

A marcha humana: circuitos neuronais entre estruturas corticais vs sub-corticais

As conexões entre os níveis corticais e sub-corticais na activação da marcha Humana carecem de discussão. As alterações da marcha por lesão no território da Artéria Cerebral Média (ACM) podem ser explicadas pela disfunção de circuitos neuronais dos Núcleos da Base ao córtex e Núcleos Pedúnculo-Pontino. Este trabalho tem como objectivo identificar os percursos anatómicos das principais conexões entre as estruturas encefálicas referidas no território da ACM. Com base na topografia das conexões neuronais, é aceitável que as alterações da marcha sejam explicadas por alterações na função dos Núcleos da Base, através das suas conexões, enquanto moduladores da actividade motora.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Estudo electromiográfico do conflito sub-acromial

Objectivo: estudar a actividade muscular no complexo articular do ombro e tronco durante o serviço e a sua relação com o Conflito Sub-Acromial. Metodologia: estudo observacional, analítico, transversal. Amostra de 15 atletas de voleibol distribuídas em 3 grupos e avaliadas através de electromiografia de superfície em músculos do ombro e do tronco. Foi avaliada a percentagem de activação muscular nas diferentes fases do serviço. Resultados: aumento de actividade do Trapézio Superior e Infraespinhoso e diminuição do Recto Abdominal e Oblíquo Externo no grupo com Conflito Sub-Acromial. Conclusão: existem diferenças significativas nas atletas com e sem Conflito Sub-Acromial.

Optimization techniques for power distribution planning with uncertainties: a comparative study

Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

O efeito da inibição dos músculos Sub-occipitais na dor cervical e de cabeça e nas amplitudes articulares

Caso clínico: Este estudo observacional descritivo - tipo estudo de caso, tem como amostra uma senhora de 36 anos com dor cervical superior esquerda e de cabeça. Após uma avaliação inicial, a paciente foi submetida a três aplicações da técnica de inibição dos músculos sub-occipitais durante uma semana em dias alternados, com o objetivo de quantificar o seu efeito nas amplitudes articulares cervicais, na dor e na funcionalidade. Para o efeito foram utilizados como instrumentos o Cervical Range of Motion Instrument, a Escala Visual Analógica e o Índice de Incapacidade relacionada com a Cervical. A paciente foi reavaliada em três momentos distintos (1’ após a primeira aplicação da técnica e oito e quinze dias depois). O resultado imediato da técnica foi de um ligeiro aumento nalgumas amplitudes articulares mas noutras ocorreu uma diminuição dos seus valores. Após 8 e 15 dias houve um aumento de todas as amplitudes articulares cervicais à exceção da inclinação e da rotação esquerda que diminuíram ligeiramente em relação à avaliação inicial e da extensão que manteve a mesma amplitude articular. Quanto à sintomatologia dolorosa foi eliminada por completo e a pontuação da funcionalidade passou de 18 para zero logo após a primeira intervenção. A aplicação desta técnica, nesta paciente, aumentou as amplitudes articulares cervicais, eliminou a dor cervical e de cabeça e melhorou a funcionalidade.