929 resultados para Elementary particle
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Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.
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The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.
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We investigate the phase behaviour of 2D mixtures of bi-functional and three-functional patchy particles and 3D mixtures of bi-functional and tetra-functional patchy particles by means of Monte Carlo simulations and Wertheim theory. We start by computing the critical points of the pure systems and then we investigate how the critical parameters change upon lowering the temperature. We extend the successive umbrella sampling method to mixtures to make it possible to extract information about the phase behaviour of the system at a fixed temperature for the whole range of densities and compositions of interest. (C) 2013 AIP Publishing LLC.
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The development of children's school achievements in mathematics is one of the most important aims of education in Poland. The results of research concerning monitoring of school achievements in maths is not optimistic. We can observe low levels of children’s understanding of the merits of maths, self-developed strategies in solving problems and practical usage of maths skills. This article frames the discussion of this problem in its psychological and didactic context and analyses the causes as they relate to school practice in teaching maths
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To determine self-consistently the time evolution of particle size and their number density in situ multi-angle polarization-sensitive laser light scattering was used. Cross-polarization intensities (incident and scattered light intensities with opposite polarization) measured at 135 degrees and ex situ transmission electronic microscopy analysis demonstrate the existence of nonspherical agglomerates during the early phase of agglomeration. Later in the particle time development both techniques reveal spherical particles again. The presence of strong cross-polarization intensities is accompanied by low-frequency instabilities detected on the scattered light intensities and plasma emission. It is found that the particle radius and particle number density during the agglomeration phase can be well described by the Brownian free molecule coagulation model. Application of this neutral particle coagulation model is justified by calculation of the particle charge whereby it is shown that particles of a few tens of nanometer can be considered as neutral under our experimental conditions. The measured particle dispersion can be well described by a Brownian free molecule coagulation model including a log-normal particle size distribution. (C) 1996 American Institute of Physics.
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Social concerns for environmental impact on air, water and soil pollution have grown along with the accelerated growth of pig production. This study intends to characterize air contamination caused by fungi and particles in swine production, and, additionally, to conclude about their eventual environmental impact. Fiftysix air samples of 50 litters were collected through impaction method. Air sampling and particle matter concentration were performed in indoor and also outdoor premises. Simultaneously, temperature and relative humidity were monitored according to the International Standard ISO 7726 – 1998. Aspergillus versicolor presents the highest indoor spore counts (>2000 CFU/m3) and the highest overall prevalence (40.5%), followed by Scopulariopsis brevicaulis (17.0%) and Penicillium sp. (14.1%). All the swine farms showed indoor fungal species different from the ones identified outdoors and the most frequent genera were also different from the ones indoors. The distribution of particle size showed the same tendency in all swine farms (higher concentration values in PM5 and PM10 sizes). Through the ratio between the indoor and outdoor values, it was possible to conclude that CFU/m3 and particles presented an eventual impact in outdoor measurements.
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Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyzethe MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems.
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Competitive electricity markets have arisen as a result of power-sector restructuration and power-system deregulation. The players participating in competitive electricity markets must define strategies and make decisions using all the available information and business opportunities.
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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.
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This paper studies a discrete dynamical system of interacting particles that evolve by interacting among them. The computational model is an abstraction of the natural world, and real systems can range from the huge cosmological scale down to the scale of biological cell, or even molecules. Different conditions for the system evolution are tested. The emerging patterns are analysed by means of fractal dimension and entropy measures. It is observed that the population of particles evolves towards geometrical objects with a fractal nature. Moreover, the time signature of the entropy can be interpreted at the light of complex dynamical systems.
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This manuscript analyses the data generated by a Zero Length Column (ZLC) diffusion experimental set-up, for 1,3 Di-isopropyl benzene in a 100% alumina matrix with variable particle size. The time evolution of the phenomena resembles those of fractional order systems, namely those with a fast initial transient followed by long and slow tails. The experimental measurements are best fitted with the Harris model revealing a power law behavior.
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Collective behaviours can be observed in both natural and man-made systems composed of a large number of elemental subsystems. Typically, each elemental subsystem has its own dynamics but, whenever interaction between individuals occurs, the individual behaviours tend to be relaxed, and collective behaviours emerge. In this paper, the collective behaviour of a large-scale system composed of several coupled elemental particles is analysed. The dynamics of the particles are governed by the same type of equations but having different parameter values and initial conditions. Coupling between particles is based on statistical feedback, which means that each particle is affected by the average behaviour of its neighbours. It is shown that the global system may unveil several types of collective behaviours, corresponding to partial synchronisation, characterised by the existence of several clusters of synchronised subsystems, and global synchronisation between particles, where all the elemental particles synchronise completely.
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Environment monitoring has an important role in occupational exposure assessment. However, due to several factors is done with insufficient frequency and normally don´t give the necessary information to choose the most adequate safety measures to avoid or control exposure. Identifying all the tasks developed in each workplace and conducting a task-based exposure assessment help to refine the exposure characterization and reduce assessment errors. A task-based assessment can provide also a better evaluation of exposure variability, instead of assessing personal exposures using continuous 8-hour time weighted average measurements. Health effects related with exposure to particles have mainly been investigated with mass-measuring instruments or gravimetric analysis. However, more recently, there are some studies that support that size distribution and particle number concentration may have advantages over particle mass concentration for assessing the health effects of airborne particles. Several exposure assessments were performed in different occupational settings (bakery, grill house, cork industry and horse stable) and were applied these two resources: task-based exposure assessment and particle number concentration by size. The results showed interesting results: task-based approach applied permitted to identify the tasks with higher exposure to the smaller particles (0.3 μm) in the different occupational settings. The data obtained allow more concrete and effective risk assessment and the identification of priorities for safety investments.
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OBJECTIVE To comprehend the perception of body image in adolescence. METHODS A qualitative study was conducted with eight focus groups with 96 students of both sexes attending four public elementary school institutions in the city of Rio de Janeiro, Southeastern Brazil, in 2013. An interview guide with questions about the adolescents’ feelings in relation to: their bodies, standards of idealized beauty, practice of physical exercise and sociocultural influences on self-image. In the data analysis we sought to understand and interpret the meanings and contradictions of narratives, understanding the subjects’ context and reasons and the internal logic of the group. RESULTS Three thematic categories were identified. The influence of media on body image showed the difficulty of achieving the perfect body and is viewed with suspicion in face of standards of beauty broadcast; the importance of a healthy body was observed as standards of beauty and good looks were closely linked to good physical condition and result from having a healthy body; the relationship between the standard of beauty and prejudice, as people who are not considered attractive, having small physical imperfections, are discriminated against and can be rejected or even excluded from society. CONCLUSIONS The standard of perfect body propagated by media influences adolescents’ self-image and, consequently, self-esteem and is considered an unattainable goal, corresponding to a standard of beauty described as artificial and unreal. However, it causes great suffering and discrimination against those who do not feel they are attractive, which can lead to health problems resulting from low self-esteem.