17 resultados para R-curve
em Instituto Politécnico do Porto, Portugal
Resumo:
The mode III interlaminar fracture of carbon/epoxy laminates was evaluated with the edge crack torsion (ECT) test. Three-dimensional finite element analyses were performed in order to select two specimen geometries and an experimental data reduction scheme. Test results showed considerable non-linearity before the maximum load point and a significant R-curve effect. These features prevented an accurate definition of the initiation point. Nevertheless, analyses of non-linearity zones showed two likely initiation points corresponding to GIIIc values between 850 and 1100 J/m2 for both specimen geometries. Although any of these values is realistic, the range is too broad, thus showing the limitations of the ECT test and the need for further research.
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Dissertação para obtenção do Grau de Mestre em Auditoria
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Dissertação apresentada ao Instituto Superior de Contabilidade para a obtenção do Grau de Mestre em Auditoria Orientador: Mestre Agostinho Sousa Pinto
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In the standard Schumpeterian-growth models only follower firms invest in R&D activities and larger economies grow faster. Since these results are counterfactual, this paper reveals that leader firms often support R&D activities and economic growth can be independent of the market size. In particular, the maintenance of R&D leadership increases with: (i) the technological-knowledge gap between leader and followers, since a firm-specific learning effect of accumulated technological knowledge from past R&D is considered, (ii) the leaders’ strategies that delay the next successful R&D supported by some follower firm, (iii) the market size, and (iv) the up-grade of each innovation.
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The development of new products or processes involves the creation, re-creation and integration of conceptual models from the related scientific and technical domains. Particularly, in the context of collaborative networks of organisations (CNO) (e.g. a multi-partner, international project) such developments can be seriously hindered by conceptual misunderstandings and misalignments, resulting from participants with different backgrounds or organisational cultures, for example. The research described in this article addresses this problem by proposing a method and the tools to support the collaborative development of shared conceptualisations in the context of a collaborative network of organisations. The theoretical model is based on a socio-semantic perspective, while the method is inspired by the conceptual integration theory from the cognitive semantics field. The modelling environment is built upon a semantic wiki platform. The majority of the article is devoted to developing an informal ontology in the context of a European R&D project, studied using action research. The case study results validated the logical structure of the method and showed the utility of the method.
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A new general fitting method based on the Self-Similar (SS) organization of random sequences is presented. The proposed analytical function helps to fit the response of many complex systems when their recorded data form a self-similar curve. The verified SS principle opens new possibilities for the fitting of economical, meteorological and other complex data when the mathematical model is absent but the reduced description in terms of some universal set of the fitting parameters is necessary. This fitting function is verified on economical (price of a commodity versus time) and weather (the Earth’s mean temperature surface data versus time) and for these nontrivial cases it becomes possible to receive a very good fit of initial data set. The general conditions of application of this fitting method describing the response of many complex systems and the forecast possibilities are discussed.
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We present a 12*(1+|R|/(4m))-speed algorithm for scheduling constrained-deadline sporadic real-time tasks on a multiprocessor comprising m processors where a task may request one of |R| sequentially-reusable shared resources.
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Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.
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In this work, cluster analysis is applied to a real dataset of biological features of several Portuguese reservoirs. All the statistical analysis is done using R statistical software. Several metrics and methods were explored, as well as the combination of Euclidean metric and the hierarchical Ward method. Although it did not present the best combination in terms of internal and stability validation, it was still a good solution and presented good results in terms of interpretation of the problem at hand.
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Trabalho de natureza profissional para a atribuição do Título de Especialista do Instituto Politécnico do Porto, na área de Línguas e Cuturas - Línguas e Literaturas Estrangeiras, defendido a 11-11-2015.
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We present stochastic dynamics on the production costs of Cournot competitions, based on perfect Nash equilibria of nonlinear R&D investment strategies to reduce the production costs of the firms at every period of the game. We analyse the effects that the R&D investment strategies can have in the profits of the firms along the time. We observe that, in certain cases, the uncertainty can improve the effects of the R&D strategies in the profits of the firms due to the non-linearity of the profit functions and also of the R&D parameters.
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We present a new R&D investment in a Cournot Duopoly model and we analyze the different possible types of Nash R&D investments. We observe that the new production costs region can be decomposed in three economical regions, depending on the Nash R&D investment, showing the relevance of the use of patents in new technologies.
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The adhesive bonding technique enables both weight and complexity reduction in structures that require some joining technique to be used on account of fabrication/component shape issues. Because of this, adhesive bonding is also one of the main repair methods for metal and composite structures by the strap and scarf configurations. The availability of strength prediction techniques for adhesive joints is essential for their generalized application and it can rely on different approaches, such as mechanics of materials, conventional fracture mechanics or damage mechanics. These two last techniques depend on the measurement of the fracture toughness (GC) of materials. Within the framework of damage mechanics, a valid option is the use of Cohesive Zone Modelling (CZM) coupled with Finite Element (FE) analyses. In this work, CZM laws for adhesive joints considering three adhesives with varying ductility were estimated. The End-Notched Flexure (ENF) test geometry was selected based on overall test simplicity and results accuracy. The adhesives Araldite® AV138, Araldite® 2015 and Sikaforce® 7752 were studied between high-strength aluminium adherends. Estimation of the CZM laws was carried out by an inverse methodology based on a curve fitting procedure, which enabled a precise estimation of the adhesive joints’ behaviour. The work allowed to conclude that a unique set of shear fracture toughness (GIIC) and shear cohesive strength (ts0) exists for each specimen that accurately reproduces the adhesive layer’ behaviour. With this information, the accurate strength prediction of adhesive joints in shear is made possible by CZM.