991 resultados para Nonlinear electric behaviour
Resumo:
The injection process of glass fibres reinforced plastics promotes the moulds surface degradation by erosion. In order to improve its wear resistance, several kinds of PVD thin hard coatings were used. It is well-known that nanostructures present a better compromise between hardness and toughness. Indeed, when the coating is constituted by a large number of ultra-thin different layers, cracks and interface troubles tend to decrease. However, it is not clear that these nanostructures present a better wear behaviour in erosion processes. In order to study its wear behaviour, a sputtered PVD nanostructured TiAlCrSiN coating was used. The substrate and film surfaces topography were analyzed by profilometry and atomic force microscopy techniques. Film adhesion to the substrate was evaluated by scratch tests. The surface hardness was measured with a Vickers micro-hardness tester. The wear resistance was evaluated by micro-abrasion with a rotating ball tribometer tests. Slurry of SiC particles in distilled water was used in order to provoke the surface abrasion. Different duration tests were performed in order to analyze the wear evolution. After these tests, the wear mechanisms developed were analyzed by scanning electron microscopy. Wear craters were measured and the wear rate was calculated and discussed. With the same purpose, coated inserts were mounted in an injection mould working with a 30% glass fibres reinforced polypropylene. After 45 000 cycles no relevant wear was registered.
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In recent years, significant research in the field of electrochemistry was developed. The performance of electrical devices, depending on the processes of the electrolytes, was described and the physical origin of each parameter was established. However, the influence of the irregularity of the electrodes was not a subject of study and only recently this problem became relevant in the viewpoint of fractional calculus. This paper describes an electrolytic process in the perspective of fractional order capacitors. In this line of thought, are developed several experiments for measuring the electrical impedance of the devices. The results are analyzed through the frequency response, revealing capacitances of fractional order that can constitute an alternative to the classical integer order elements. Fractional order electric circuits are used to model and study the performance of the electrolyte processes.
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The development of fractional-order controllers is currently one of the most promising fields of research. However, most of the work in this area addresses the case of linear systems. This paper reports on the analysis of fractional-order control of nonlinear systems. The performance of discrete fractional-order PID controllers in the presence of several nonlinearities is discussed. Some results are provided that indicate the superior robustness of such algorithms.
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Sera of persons of different age groups collected in 1976, 1978 and 1979 were tested for the presence of HI antibodies against various strains of the H3N2 and H1N1 subtypes of influenza virus. The occurrence of infection by H3N2 subtype was recorded during the 1976-1978 period but in 1979, circulation of this subtype of virus was limited. The prevalence of antibody against A/São Paulo/1/78 (H1N1) was significantly higher than that of antibody to A/USSB/90/77 (HIND in 1978. However in 1979 the predominant strain was A/USSR/90/77 (HIND. Persons under 20 years of age were the most affected by H1N1 subtype. Antibodies to H1N1 subtype were detected in sera of individuals older than 20 years in 1976, before the re-emergence of this strain. Serological results indicate that infections by H3N2 subtype in 1978 occurred in 65.4% of young children (0-4 year group). About 47.0% of children from the 0-4 year group had antibodies to H1N1 subtype in 1979. Antibodies to swine influenza virus were detected in 60% of 60+ year old people.
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Hamster inoculated intraperitoneally with 1 x 10(7) parasites of L. donovani and L. major-like of the New World were studied in groups of 15, 30, 60 and 90 days of infection. The parasite load and density showed progressive increase with the evolution of the infection and was higher in the L. donovani groups than in the L. major-like groups. The L. major-like groups showed parasite density higher in the spleen than in the liver and was similar in both organs in L. donovani groups. The histopathology showed a diffuse marked hyperplasia and hypertrophy of the reticuloendothelial system with high parasitism in the L. donovani groups while there was focal involvement of these organs in L. major-like groups, forming nodules of macrophages that were scantly parasitised. The biological behaviour could be useful in the preliminary studies of Leishmania strain in regional laboratories and understanding the histopathology of lesions caused by different leishmania species.
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In this study the effect of incorporation of recycled glass-fibre reinforced polymer (GFRP) waste materials, obtained by means of milling processes, on mechanical behaviour of polyester polymer mortars was assessed. For this purpose, different contents of recycled GFRP waste powder and fibres, with distinct size gradings, were incorporated into polyester based mortars as sand aggregates and filler replacements. Flexural and compressive loading capacities were evaluated and found better than unmodified polymer mortars. GFRP modified polyester based mortars also show a less brittle behaviour, with retention of some loading capacity after peak load. Obtained results highlight the high potential of recycled GFRP waste materials as efficient and sustainable reinforcement and admixture for polymer concrete and mortars composites, constituting an emergent waste management solution.
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This paper presents the system developed to promote the rational use of electric energy among consumers and, thus, increase the energy efficiency. The goal is to provide energy consumers with an application that displays the energy consumption/production profiles, sets up consuming ceilings, defines automatic alerts and alarms, compares anonymously consumers with identical energy usage profiles by region and predicts, in the case of non-residential installations, the expected consumption/production values. The resulting distributed system is organized in two main blocks: front-end and back-end. The front-end includes user interface applications for Android mobile devices and Web browsers. The back-end provides data storage and processing functionalities and is installed in a cloud computing platform - the Google App Engine - which provides a standard Web service interface. This option ensures interoperability, scalability and robustness to the system.
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This paper evaluates the influence of two superplasticizers (SP) on the rheological behaviour of concrete made with fine recycled concrete aggregates (FRCA). Three families of concrete were tested: family CO made without SP, family Cl made with a regular superplasticizer and family C2 made with a high-performance superplasticizer. Five replacement ratios of natural sand by FRCA were tested: 0%, 10%, 30%, 50% and 100%. The coarse aggregates were natural gravels. Three criteria were established to design the concrete mixes' composition: keep the same particle size distribution curves, adjust the water/cement ratio to obtain a similar slump and no pre-saturation of the FRCA. All mixes had the same cement and SP content. The results show that the incorporation of FRCA significantly increased the shrinkage and creep deformation. The FRCA's effect was influenced by the curing age. The reference concrete made with natural sand stabilizes the creep deformation faster than the mixes made with FRCA. The incorporation of superplasticizer increased the shrinkage at early ages and decreased the shrinkage at 91 days of age. The regular superplasticizer did not improve the creep deformation while the high-performance superplasticizer highly improved this property. The incorporation of FRCA jeopardized the SP's effectiveness. This study demonstrated that to use FRCA and superplasticizer for concrete production it is necessary to take into account the different rheological behaviour of these mixes. (C) 2015 Elsevier Ltd. All rights reserved.
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This paper presents the project of a mobile cockpit system (MCS) for smartphones, which provides assistance to electric bicycle (EB) cyclists in smart cities' environment. The presented system introduces a mobile application (MCS App) with the goal to provide useful personalized information to the cyclist related to the EB's use, including EB range prediction considering the intended path, management of the cycling effort performed by the cyclist, handling of the battery charging process, and the provisioning of information regarding available public transport. This work also introduces the EB cyclist profile concept, which is based on historical data analysis previously stored in a database and collected from mobile devices' sensors. From the tests performed, the results show the importance of route guidance, taking into account the energy savings. The results also show significant changes on range prediction based on user and route taken. It is important to say that the proposed system can be used for all bicycles in general.
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The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.
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The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.
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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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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.
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Mg alloys are very susceptible to corrosion in physiological media. This behaviour limits its widespread use in biomedical applications as bioresorbable implants, but it can be controlled by applying protective coatings. On one hand, coatings must delay and control the degradation process of the bare alloy and, on the other hand, they must be functional and biocompatible. In this study a biocompatible polycaprolactone (PCL) coating was functionalised with nano hydroxyapatite (HA) particles for enhanced biocompatibility and with an antibiotic, cephalexin, for anti-bacterial purposes and applied on the AZ31 alloy. The chemical composition and the surface morphology of the coated samples, before and after the corrosion tests, were studied by scanning electron microscopy (SEM) coupled with energy dispersive x-ray analysis (EDX) and Raman. The results showed that the presence of additives induced the formation of agglomerates and defects in the coating that resulted in the formation of pores during immersion in Hanks' solution. The corrosion resistance of the coated samples was studied in Hank's solution by electrochemical impedance spectroscopy (EIS). The results evidenced that all the coatings can provide corrosion protection of the bare alloy. However, in the presence of the additives, corrosion protection decreased. The wetting behaviour of the coating was evaluated by the static contact angle method and it was found that the presence of both hydroxyapatite and cephalexin increased the hydrophilic behaviour of the surface. The results showed that it is possible to tailor a composite coating that can store an antibiotic and nano hydroxyapatite particles, while allowing to control the in-vitro corrosion degradation of the bioresorbable Mg alloy AZ31. (C) 2015 Elsevier Ltd. All rights reserved.
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Copper iron (Cu-Fe) 3D porous foams for supercapacitor electrodes were electrodeposited in the cathodic regime, on stainless steel current collectors, using hydrogen bubbling dynamic template. The foams were prepared at different current densities and deposition times. The foams were submitted to thermal conditioning at temperatures of 150 and 250 degrees C. The morphology, composition and structure of the formed films were studied by SEM, EDS and XRD, respectively. The electrochemical behaviour was studied by cyclic voltammetry, electrochemical impedance spectroscopy and chronopotentiometry. The morphology of the 3D Cu-Fe foams is sensitive to the electrodeposition current and time. The increase of the current density produces a denser, larger and more ramified dendritic structure. Thermal conditioning at high temperature induces a coarser grain structure and the formation of copper oxides, which affect the electrochemical behaviour. The electrochemical response reveals the presence of various redox peaks assigned to the oxidation and reduction of Cu and Fe oxides and hydroxides in the foams. The specific capacitance of the 3D Cu Fe foams was significantly enhanced by thermal conditioning at 150 degrees C. The highest specific capacitance values attained 297 Fg(-1) which are much above the ones typically observed for single Cu or Fe Oxides and hydroxides. These values highlight a synergistic behaviour resulting from the combination of Cu and Fe in the form of nanostructured metallic foams. Moreover, the capacitance retention observed in an 8000 charge/discharge cycling test was above 66%, stating the good performance of these materials and its enhanced electrochemical response as supercapacitor negative electrodes. (C) 2014 Elsevier B.V. All rights reserved.