7 resultados para reinforcement classes

em Instituto Politécnico do Porto, Portugal


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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 is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

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The development and applications of thermoset polymeric composites, namely fiber reinforced polymers (FRP), have shifted in the last decades more and more into the mass market [1]. Production and consume have increased tremendously mainly for the construction, transportation and automobile sectors [2, 3]. Although the many successful uses of thermoset composite materials, recycling process of byproducts and end of lifecycle products constitutes a more difficult issue. The perceived lack of recyclability of composite materials is now increasingly important and seen as a key barrier to the development or even continued used of these materials in some markets.

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Glass fibre-reinforced plastics (GFRP), nowadays commonly used in the construction, transportation and automobile sectors, have been considered inherently difficult to recycle due to both: cross-linked nature of thermoset resins, which cannot be remolded, and complex composition of the composite itself, which includes glass fibres, matrix and different types of inorganic fillers. Presently, most of the GFRP waste is landfilled leading to negative environmental impacts and supplementary added costs. With an increasing awareness of environmental matters and the subsequent desire to save resources, recycling would convert an expensive waste disposal into a profitable reusable material. There are several methods to recycle GFR thermostable materials: (a) incineration, with partial energy recovery due to the heat generated during organic part combustion; (b) thermal and/or chemical recycling, such as solvolysis, pyrolisis and similar thermal decomposition processes, with glass fibre recovering; and (c) mechanical recycling or size reduction, in which the material is subjected to a milling process in order to obtain a specific grain size that makes the material suitable as reinforcement in new formulations. This last method has important advantages over the previous ones: there is no atmospheric pollution by gas emission, a much simpler equipment is required as compared with ovens necessary for thermal recycling processes, and does not require the use of chemical solvents with subsequent environmental impacts. In this study the effect of incorporation of recycled GFRP waste materials, obtained by means of milling processes, on mechanical behavior of polyester polymer mortars was assessed. For this purpose, different contents of recycled GFRP waste materials, with distinct size gradings, were incorporated into polyester polymer mortars as sand aggregates and filler replacements. The effect of GFRP waste treatment with silane coupling agent was also assessed. Design of experiments and data treatment were accomplish by means of factorial design and analysis of variance ANOVA. The use of factorial experiment design, instead of the one-factor-at-a-time method is efficient at allowing the evaluation of the effects and possible interactions of the different material factors involved. Experimental results were promising toward the recyclability of GFRP waste materials as aggregates and filler replacements for polymer mortar, with significant gain of mechanical properties with regard to non-modified polymer mortars.

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This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.

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Rehabilitation is becoming more and more usual in the construction sector in Portugal. The introduction of newer construction materials and technical know-how of integrating different materials for achieving desired engineering goals is an important step to the development of the sector. Wood industry is also getting more and more adapted to composite technologies with the introduction of the so called “highly engineered wood products” and with the use of modification treatments. This work is an attempt to explain the viability of using stainless steel and glass fibre reinforced polymer (GFRP) as reinforcements in wood beams. This thesis specifically focuses on the flexural behaviour of Portuguese Pine unmodified and modified wood beams. Two types of modification were used: 1,3-dimethylol-4,5- dihydroxyethyleneurea (DMDHEU) resin and amid wax. The behaviour of the material was analysed with a nonlinear model. The latter model simulates the behaviour of the reinforced wood beams under flexural loading. Small-scale beams (1:15) were experimented in flexural bending and the experimental results obtained were compared with the analytical model results. The experiments confirm the viability of the reinforcing schemes and the working procedures. Experimental results showed fair agreement with the nonlinear model. A strength increase between 15% and 80% was achieved. Stiffness increased by 40% to 50% in beams reinforced with steel but no significant increase was achieved with the glass fibre reinforcement.

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It is well recognized that professional musicians are at risk of hearing damage due to the exposure to high sound pressure levels during music playing. However, it is important to recognize that the musicians’ exposure may start early in the course of their training as students in the classroom and at home. Studies regarding sound exposure of music students and their hearing disorders are scarce and do not take into account important influencing variables. Therefore, this study aimed to describe sound level exposures of music students at different music styles, classes, and according to the instrument played. Further, this investigation attempted to analyze the perceptions of students in relation to exposure to loud music and consequent health risks, as well as to characterize preventive behaviors. The results showed that music students are exposed to high sound levels in the course of their academic activity. This exposure is potentiated by practice outside the school and other external activities. Differences were found between music style, instruments, and classes. Tinnitus, hyperacusis, diplacusis, and sound distortion were reported by the students. However, students were not entirely aware of the health risks related to exposure to high sound pressure levels. These findings reflect the importance of starting intervention in relation to noise risk reduction at an early stage, when musicians are commencing their activity as students.

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The purpose of this study was to analyse differences between total physical activity (TPA) and moderate-to-vigorous PA (MVPA) of pre-school children during daily school hours when they attended the physical education class (PED) and school days without PE class (NPED) and to assess the contribution of PE classes to TPA in school hours. The sample was composed of 193 pre-school healthy children (96 girls) aged from three to five years old and was conducted between February and December of 2008. Children wore accelerometers for at least four consecutive days during school hours. Data were analysed with specific software, age-specific counts-per-minute cut-off points and a 5 s epoch were used. Independent and general linear model repeated measures were used to assess differences between gender and differences between different days within each gender, respectively. Boys engaged more MVPA than girls (P < 0.05). During PED, pre-school children engaged significantly more in TPA and MVPA than during NPED (P < 0.05). PE class contributed, on average, 27.7% for the TPA and 32.8% of daily MVPA during PED in both gender. The results of this study suggest that structured PA such as a PE class increased the daily TPA and MVPA level of pre-school children.