116 resultados para Numerical optimization


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This study addresses the optimization of rational fraction approximations for the discrete-time calculation of fractional derivatives. The article starts by analyzing the standard techniques based on Taylor series and Padé expansions. In a second phase the paper re-evaluates the problem in an optimization perspective by tacking advantage of the flexibility of the genetic algorithms.

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This paper addresses the calculation of fractional order expressions through rational fractions. The article starts by analyzing the techniques adopted in the continuous to discrete time conversion. The problem is re-evaluated in an optimization perspective by tacking advantage of the degree of freedom provided by the generalized mean formula. The results demonstrate the superior performance of the new algorithm.

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Several phenomena present in electrical systems motivated the development of comprehensive models based on the theory of fractional calculus (FC). Bearing these ideas in mind, in this work are applied the FC concepts to define, and to evaluate, the electrical potential of fractional order, based in a genetic algorithm optimization scheme. The feasibility and the convergence of the proposed method are evaluated.

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This paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with a distinct fitness function, is established.

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Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

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A utilização de juntas coladas em aplicações industriais tem vindo a aumentar nos últimos anos, em detrimento dos métodos tradicionais de ligação tais como a soldadura, brasagem, ligações aparafusadas e rebitadas. As juntas de sobreposição simples são o tipo de juntas mais frequentemente utilizadas em aplicações industriais, porque são as mais simples de fabricar. No entanto, a aplicação descentrada da carga neste tipo de junta provoca efeitos de flexão que originam o aparecimento de tensões normais na direção da espessura do adesivo (arrancamento), reduzindo assim a resistência da junta colada. De uma maneira geral, existem dois tipos de métodos para reduzir as concentrações de tensões. O primeiro é utilizar alterações no próprio material, otimizando as propriedades do adesivo e do substrato, enquanto o segundo método envolve alterar a geometria da junta, como por exemplo utilizando filetes de adesivo, chanfros nas extremidades dos substratos, aplicar uma geometria ondulada ou dobrar os substratos na zona de sobreposição, ou ainda utilizar rasgos nos substratos ao longo da sobreposição. Neste trabalho é realizado um estudo experimental e numérico por Elementos Finitos de duas alterações efetuadas à geometria de juntas de sobreposição simples, de modo a aumentar a sua resistência comparativamente às juntas sem alteração geométrica. A primeira condição efetuada foi a utilização de rasgos nas extremidades do comprimento de sobreposição e a segunda foi a utilização de rasgos a meio do comprimento de sobreposição. No final do estudo experimental, verificou-se que a resistência da ligação foi significativamente melhorada com algumas das configurações testadas para cada alteração, e foi possível estabelecer em ambos os casos a configuração ótima. Numa fase posterior, procedeu-se à simulação numérica, que incluiu uma análise de tensões e previsão do comportamento das juntas através de modelos de dano coesivo. A análise permitiu obter os modos de rotura, as curvas força-deslocamento e a resistência das juntas. Obteve-se uma concordância bastante boa com os resultados experimentais, o que mostrou a adequabilidade do método de previsão proposto para estimar o comportamento das juntas.

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This paper presents an optimization approach for the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The proposed approach is based on a genetic algorithm technique. The scheduling rules such as SPT and MWKR are integrated into the process of genetic evolution. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities and delay times of the operations are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed approach.

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The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms are needed. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms. The results are compared with a genetic algorithm that adopts the direct kinematics. In both cases the trajectory planning is formulated as an optimization problem with constraints.

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Buildings account for 40% of total energy consumption in the European Union. The reduction of energy consumption in the buildings sector constitute an important measure needed to reduce the Union's energy dependency and greenhouse gas emissions. The Portuguese legislation incorporate this principles in order to regulate the energy performance of buildings. This energy performance should be accompanied by good conditions for the occupants of the buildings. According to EN 15251 (2007) the four factors that affect the occupant comfort in the buildings are: Indoor Air Quality (IAQ), thermal comfort, acoustics and lighting. Ventilation directly affects all except the lighting, so it is crucial to understand the performance of it. The ventilation efficiency concept therefore earn significance, because it is an attempt to quantify a parameter that can easily distinguish the different options for air diffusion in the spaces. The two indicators most internationally accepted are the Air Change Efficiency (ACE) and the Contaminant Removal Effectiveness (CRE). Nowadays with the developed of the Computational Fluid Dynamics (CFD) the behaviour of ventilation can be more easily predicted. Thirteen strategies of air diffusion were measured in a test chamber through the application of the tracer gas method, with the objective to validate the calculation by the MicroFlo module of the IES-VE software for this two indicators. The main conclusions from this work were: that the values of the numerical simulations are in agreement with experimental measurements; the value of the CRE is more dependent of the position of the contamination source, that the strategy used for the air diffusion; the ACE indicator is more appropriate for quantifying the quality of the air diffusion; the solutions to be adopted, to maximize the ventilation efficiency should be, the schemes that operate with low speeds of supply air and small differences between supply air temperature and the room temperature.

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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 polymer mortar aggregates, without significant loss of mechanical properties with regard to non-modified polymer mortars.

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This study addresses to the optimization of pultrusion manufacturing process from the energy-consumption point of view. The die heating system of external platen heaters commonly used in the pultrusion machines is one of the components that contribute the most to the high consumption of energy of pultrusion process. Hence, instead of the conventional multi-planar heaters, a new internal die heating system that leads to minor heat losses is proposed. The effect of the number and relative position of the embedded heaters along the die is also analysed towards the setting up of the optimum arrangement that minimizes both the energy rate and consumption. Simulation and optimization processes were greatly supported by Finite Element Analysis (FEA) and calibrated with basis on the temperature profile computed through thermography imaging techniques. The main outputs of this study allow to conclude that the use of embedded cylindrical resistances instead of external planar heaters leads to drastic reductions of both the power consumption and the warm-up periods of the die heating system. For the analysed die tool and process, savings on energy consumption up to 60% and warm-up period stages less than an half hour were attained with the new internal heating system. The improvements achieved allow reducing the power requirements on pultrusion process, and thus minimize industrial costs and contribute to a more sustainable pultrusion manufacturing industry.

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This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

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Manufacturing processes need permanently to innovate and optimize because any can be susceptible to continuous improvement. Innovation and commitment to the development of these new solutions resulting from existing expertise and the continuing need to increase productivity, flexibility and ensuring the necessary quality of the manufactured products. To increase flexibility, it is necessary to significantly reduce set-up times and lead time in order to ensure the delivery of products ever faster. This objective can be achieved through a normalization of the pultrusion line elements. Implicitly, there is an increase of productivity by this way. This work is intended to optimize the pultrusion process of structural profiles. We consider all elements of the system from the storehouse of the fibers (rack) to the pultrusion die. Particular attention was devoted to (a) the guidance system of the fibers and webs, (b) the resin container where the fibers are impregnated, (c) standard plates positioning of the fibers towards the entrance to the spinneret and also (d) reviewed the whole process of assembling and fixing the die as well as its the heating system. With the implementation of these new systems was achieved a significant saving of time set-up and were clearly reduced the unit costs of production. Quality assurance was also increased.

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The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

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Trihalomethanes (THMs) are widely referred and studied as disinfection by-products (DBPs). The THMs that are most commonly detected are chloroform (TCM), bromodichloromethane (BDCM), chlorodibromomethane (CDBM), and bromoform (TBM). Several studies regarding the determination of THMs in swimming pool water and air samples have been published. This paper reviews the most recent work in this field, with a special focus on water and air sampling, sample preparation and analytical determination methods. An experimental study has been developed in order to optimize the headspace solid-phasemicroextraction (HS-SPME) conditions of TCM, BDCM, CDBM and TBM from water samples using a 23 factorial design. An extraction temperature of 45 °C, for 25min, and a desorption time of 5 min were found to be the best conditions. Analysis was performed by gas chromatography with an electron capture detector (GC-ECD). The method was successfully applied to a set of 27 swimming pool water samples collected in the Oporto area (Portugal). TCM was the only THM detected with levels between 4.5 and 406.5 μg L−1. Four of the samples exceeded the guideline value for total THMs in swimming pool water (100 μgL−1) indicated by the Portuguese Health Authority.