977 resultados para Renewable enrgy systems
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The aim of this study is to optimize the heat flow through the pultrusion die assembly system on the manufacturing process of a specific glass-fiber reinforced polymer (GFRP) pultrusion profile. The control of heat flow and its distribution through whole die assembly system is of vital importance in optimizing the actual GFRP pultrusion process. Through mathematical modeling of heating-die process, by means of Finite Element Analysis (FEA) program, an optimum heater selection, die position and temperature control was achieved. The thermal environment within the die was critically modeled relative not only to the applied heat sources, but also to the conductive and convective losses, as well as the thermal contribution arising from the exothermic reaction of resin matrix as it cures or polymerizes from the liquid to solid condition. Numerical simulation was validated with basis on thermographic measurements carried out on key points along the die during pultrusion process.
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The use of Laptops and the Internet has produced the technological conditions for instructors and students can take advantage from the diversity of online information, communication, collaboration and sharing with others. The integration of Internet services in the teaching practices can be responsible for thematic, social and digital improvement for the agents involved. There are many benefits when we use a Learning Management Systems (LMS) such as Moodle, to support the lectures in higher education. We also will consider its implications for student support and online interaction, leading educational agents to a collaborating of different learning environments, where they can combine face-to-face instruction with computer-mediated instruction, blended-learning, and increases the possibilities for better quality and quantity of human communication in a learning background. In general components of learning management systems contain synchronous and asynchronous communication tools, management features, and assessment utilities. These assessment utilities allow lecturers to systematize basic assessment tasks. Assessments can be straightaway delivered to the student, and upon conclusion, immediately returned with grades and detailed feedback. Therefore learning management systems can also be used for assessment purposes in Higher Education.
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Portugal é um país dependente da energia do exterior, devido à elevada percentagem de consumo de energia a partir de fontes primárias, como por exemplo o gasóleo. Para colmatar este cenário, têm vindo a criar-se incentivos para o uso de energias renováveis e para intensificação de medidas de eficiência energética, como os sistemas de cogeração, de forma a tornar os processos industriais nacionais mais autónomos e mais competitivos. O presente trabalho, centra-se na determinação do potencial térmico disponível na central de trigeração da empresa Monteiro, Ribas-Indústria, SA, com a finalidade de identificar a quantidade de energia não utilizada, com vista ao aproveitamento dessa mesma energia nos processos mais problemáticos da empresa. Verificou-se que a água líquida era a fonte de maior energia não aproveitada, representando cerca de 30%, relativamente à energia disponível na água de refrigeração que é de 1890 kW. Assim, perante este facto, fez-se um estudo em dois setores autónomos da empresa, o setor dos revestimentos e o setor dos componentes técnicos da borracha. Pretendeu-se propor medidas para melhorar os seus processos produtivos, aproveitando essa energia. Para o efeito foi projetado um permutador de calor de placas com necessidade energética de 131,4 MWh, no setor dos revestimentos e um permutador compacto no setor de produção de placas de borracha, necessitando de uma energia de 335,2 MWh. Face à energia disponível na central de trigeração, de 161,9 MWh, verifica-se que esta apenas poderá ser aproveitada no setor dos revestimentos. Para tornar este objetivo real, a empresa Monteiro, Ribas- Indústria, SA necessitaria de efetuar um investimento no total de 49.390€. Além disso, foi contabilizado o rendimento das caldeiras da central térmica e da cogeração, ambas pelo método direto, apresentando estas os valores de 72% e 42%, respectivamente.
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
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Hydraulic systems are dynamically susceptible in the presence of entrapped air pockets, leading to amplified transient reactions. In order to model the dynamic action of an entrapped air pocket in a confined system, a heuristic mathematical formulation based on a conceptual analogy to a mechanical spring-damper system is proposed. The formulation is based on the polytropic relationship of an ideal gas and includes an additional term, which encompasses the combined damping effects associated with the thermodynamic deviations from the theoretical transformation, as well as those arising from the transient vorticity developed in both fluid domains (air and water). These effects represent the key factors that account for flow energy dissipation and pressure damping. Model validation was completed via numerical simulation of experimental measurements.
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Dynamic and distributed environments are hard to model since they suffer from unexpected changes, incomplete knowledge, and conflicting perspectives and, thus, call for appropriate knowledge representation and reasoning (KRR) systems. Such KRR systems must handle sets of dynamic beliefs, be sensitive to communicated and perceived changes in the environment and, consequently, may have to drop current beliefs in face of new findings or disregard any new data that conflicts with stronger convictions held by the system. Not only do they need to represent and reason with beliefs, but also they must perform belief revision to maintain the overall consistency of the knowledge base. One way of developing such systems is to use reason maintenance systems (RMS). In this paper we provide an overview of the most representative types of RMS, which are also known as truth maintenance systems (TMS), which are computational instances of the foundations-based theory of belief revision. An RMS module works together with a problem solver. The latter feeds the RMS with assumptions (core beliefs) and conclusions (derived beliefs), which are accompanied by their respective foundations. The role of the RMS module is to store the beliefs, associate with each belief (core or derived belief) the corresponding set of supporting foundations and maintain the consistency of the overall reasoning by keeping, for each represented belief, the current supporting justifications. Two major approaches are used to reason maintenance: single-and multiple-context reasoning systems. Although in the single-context systems, each belief is associated to the beliefs that directly generated it—the justification-based TMS (JTMS) or the logic-based TMS (LTMS), in the multiple context counterparts, each belief is associated with the minimal set of assumptions from which it can be inferred—the assumption-based TMS (ATMS) or the multiple belief reasoner (MBR).
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Decentralised co-operative multi-agent systems are computational systems where conflicts are frequent due to the nature of the represented knowledge. Negotiation methodologies, in this case argumentation based negotiation methodologies, were developed and applied to solve unforeseeable and, therefore, unavoidable conflicts. The supporting computational model is a distributed belief revision system where argumentation plays the decisive role of revision. The distributed belief revision system detects, isolates and solves, whenever possible, the identified conflicts. The detection and isolation of the conflicts is automatically performed by the distributed consistency mechanism and the resolution of the conflict, or belief revision, is achieved via argumentation. We propose and describe two argumentation protocols intended to solve different types of identified information conflicts: context dependent and context independent conflicts. While the protocol for context dependent conflicts generates new consensual alternatives, the latter chooses to adopt the soundest, strongest argument presented. The paper shows the suitability of using argumentation as a distributed decentralised belief revision protocol to solve unavoidable conflicts.
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The ability to respond sensibly to changing and conflicting beliefs is an integral part of intelligent agency. To this end, we outline the design and implementation of a Distributed Assumption-based Truth Maintenance System (DATMS) appropriate for controlling cooperative problem solving in a dynamic real world multi-agent community. Our DATMS works on the principle of local coherence which means that different agents can have different perspectives on the same fact provided that these stances are appropriately justified. The belief revision algorithm is presented, the meta-level code needed to ensure that all system-wide queries can be uniquely answered is described, and the DATMS’ implementation in a general purpose multi-agent shell is discussed.
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Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.
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Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.
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The iron(III) complexes [H(EtOH)][FeCl2(L)(2)] (1), [H(2)bipy](1/2)[FeCl2(L)(2)].DMF (2) and [FeCl2(L)(2,2'-bipy)] (3) (L = 3-amino-2-pyrazinecarboxylate; H(2)bipy = doubly protonated 4,4'-bipyridine; 2,2'-bipy = 2,2'-bipyridine, DMF = dimethylformamide) have been synthesized and fully characterized by IR, elemental and single-crystal X-ray diffraction analyses, as well as by electrochemical methods. Complexes 1 and 2 have similar mononuclear structures containing different guest molecules (protonated ethanol for 1 and doubly protonated 4,4'-bipyridine for 2) in their lattices, whereas the complex 3 has one 3-amino-2-pyrazinecarboxylate and a 2,2'-bipyridine ligand. They show a high catalytic activity for the low power (10 W) solvent-free microwave assisted peroxidative oxidation of 1-phenylethanol, leading, in the presence of TEMPO, to quantitative yields of acetophenone [TOFs up to 8.1 x 10(3) h(-1), (3)] after 1 h. Moreover, the catalysts are of easy recovery and reused, at least for four consecutive cycles, maintaining 83 % of the initial activity and concomitant rather high selectivity. 3-Amino-2-pyrazinecarboxylic acid is used to synthesize three new iron(III) complexes which act as heterogeneous catalysts for the solvent-free microwave-assisted peroxidative oxidation of 1-phenylethanol.
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Within a large set of renewable energies being explored to tackle energy sourcing problems, bioenergy can represent an attractive solution if effectively managed. The supply chain design supported by mathematical programming can be used as a decision support tool to the successful bioenergy production systems establishment. This strategic decision problem is addressed in this paper where we intent to study the design of the residual forestry biomass to bioelectricity production in the Portuguese context. In order to contribute to attain better solutions a mixed integer linear programming (MILP) model is developed and applied in order to optimize the design and planning of the bioenergy supply chain. While minimizing the total supply chain cost the production energy facilities capacity and location are defined. The model also includes the optimal selection of biomass amounts and sources, the transportation modes selection, and links that must be established for biomass transportation and products delivers to markets. Results illustrate the positive contribution of the mathematical programming approach to achieve viable economic solutions. Sensitivity analysis on the most uncertain parameters was performed: biomass availability, transportation costs, fixed operating costs and investment costs. (C) 2015 Elsevier Ltd. All rights reserved.
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he expansion of Digital Television and the convergence between conventional broadcasting and television over IP contributed to the gradual increase of the number of available channels and on demand video content. Moreover, the dissemination of the use of mobile devices like laptops, smartphones and tablets on everyday activities resulted in a shift of the traditional television viewing paradigm from the couch to everywhere, anytime from any device. Although this new scenario enables a great improvement in viewing experiences, it also brings new challenges given the overload of information that the viewer faces. Recommendation systems stand out as a possible solution to help a watcher on the selection of the content that best fits his/her preferences. This paper describes a web based system that helps the user navigating on broadcasted and online television content by implementing recommendations based on collaborative and content based filtering. The algorithms developed estimate the similarity between items and users and predict the rating that a user would assign to a particular item (television program, movie, etc.). To enable interoperability between different systems, programs characteristics (title, genre, actors, etc.) are stored according to the TV-Anytime standard. The set of recommendations produced are presented through a Web Application that allows the user to interact with the system based on the obtained recommendations.
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Dissertação apresentada na Faculdade de Ciências e Tecnologias da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores