999 resultados para Energetic optimization
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In this work we solve Mathematical Programs with Complementarity Constraints using the hyperbolic smoothing strategy. Under this approach, the complementarity condition is relaxed through the use of the hyperbolic smoothing function, involving a positive parameter that can be decreased to zero. An iterative algorithm is implemented in MATLAB language and a set of AMPL problems from MacMPEC database were tested.
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We have developed a new method for single-drop microextraction (SDME) for the preconcentration of organochlorine pesticides (OCP) from complex matrices. It is based on the use of a silicone ring at the tip of the syringe. A 5 μL drop of n-hexane is applied to an aqueous extract containing the OCP and found to be adequate to preconcentrate the OCPs prior to analysis by GC in combination with tandem mass spectrometry. Fourteen OCP were determined using this technique in combination with programmable temperature vaporization. It is shown to have many advantages over traditional split/splitless injection. The effects of kind of organic solvent, exposure time, agitation and organic drop volume were optimized. Relative recoveries range from 59 to 117 %, with repeatabilities of <15 % (coefficient of variation) were achieved. The limits of detection range from 0.002 to 0.150 μg kg−1. The method was applied to the preconcentration of OCPs in fresh strawberry, strawberry jam, and soil.
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Multiclass analysis method was optimized in order to analyze pesticides traces by gas chromatography with ion-trap and tandem mass spectrometry (GC-MS/MS). The influence of some analytical parameters on pesticide signal response was explored. Five ion trap mass spectrometry (IT-MS) operating parameters, including isolation time (IT), excitation voltage (EV), excitation time (ET),maximum excitation energy or “q” value (q), and isolationmass window (IMW) were numerically tested in order to maximize the instrument analytical signal response. For this, multiple linear regression was used in data analysis to evaluate the influence of the five parameters on the analytical response in the ion trap mass spectrometer and to predict its response. The assessment of the five parameters based on the regression equations substantially increased the sensitivity of IT-MS/MS in the MS/MS mode. The results obtained show that for most of the pesticides, these parameters have a strong influence on both signal response and detection limit.Using the optimized method, a multiclass pesticide analysis was performed for 46 pesticides in a strawberry matrix. Levels higher than the limit established for strawberries by the European Union were found in some samples.
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Dissertação de Mestrado em Ambiente, Saúde e Segurança.
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O presente trabalho tem como objectivo o diagnóstico ambiental da empresa Lacticinios do Paiva, S.A, a avaliação da água do processo e da ETARI e o estudo da fermentação do soro de queijo com o intuito de produção de bioetanol. No diagnóstico ambiental da empresa, observou-se que 18.227.731 litros de leite usados anualmente geram 5.031 ton/ano de queijo, 7.204 ton/ano de soro de queijo, 74.201 m3/ano de efluente liquido, 14 ton/ano de plástico e 20 ton/ano de cartão. Os principais problemas com necessidade de optimização são a recuperação de água das lavagens, avaliação da produção de biogás no digestor anaeróbio, recuperação do volume de leite que é desperdiçado na produção de queijo fresco de longa duração, avaliação da eficiência energética da empresa, valorização das natas e do soro de queijo. Decidiu-se neste trabalho avaliar a possibilidade de reciclagem das águas de lavagem, avaliar o funcionamento da ETARI face à legislação existente e estudar a possibilidade de valorização do soro de queijo. Na avaliação das águas de processo das lavagens para posterior reciclagem, verifica-se que relativamente ao pH e aos sólidos suspensos não existe problema, podendo encarar-se a hipótese de reciclagem directa. No entanto, no que respeita à carga orgânica das águas de lavagem do sistema de ultrafiltração do queijo fresco de longa duração, constata-se que esta não poderia ser utilizada novamente, uma vez que apresenta valores elevados de CQO. Para a sua reutilização, será necessário remover a CQO, hipótese que se estudou com resultados positivos. Verificou-se que, um tratamento por adsorção em carvão activado precedido de microfiltração, reduz a CQO de forma significativa permitindo admitir a hipótese de reciclagem da água, nomeadamente para as 1ª e 3ª águas de lavagem. As outras águas teriam necessidade de mais tempo de contacto com o carvão activado. No sentido de avaliar o funcionamento da ETARI, foram analisadas várias correntes da mesma, em particular a do efluente final, no que respeita a parâmetros como: pH, Sólidos Suspensos Totais, Carência Química de Oxigénio, Carência Bioquímica de Oxigénio, Turvação, Nitratos, Fósforo Total, Azoto Kjeldalh, Azoto Amoniacal e Cloretos. Observou-se que os valores para o efluente final da ETARI são os seguintes: pH compreendido entre [7,21 – 8,69], SST entre [65,3 – 3110] mg/L, CQO entre [92,5 – 711,5] mg/L, CBO5 entre [58 – 161] mg/L, NO3- entre [10,8 – 106,7] mg/L, fósforo total entre [8,3 – 64,3] mg/L, turvação entre [67,7 – 733,3] FTU e cloretos entre [459,9 – 619,81] mg/L; pode-se dizer que os parâmetros analisados se encontram quase sempre dentro da gama de valores impostos pela Câmara Municipal de Lamego pelo que o efluente pode ser lançado no Colector Municipal de Cambres. Relativamente à fermentação alcoólica do soro de queijo, verifica-se que a levedura Kluyveromyces Marxianus consegue degradar praticamente todo o açúcar presente no permeado produzindo assim uma quantidade razoável de etanol. Quando se utilizou a levedura Saccharomyces Cerevisiae, a produção de etanol foi muito reduzida, como esperado, dado que esta levedura apresenta dificuldades na metabolização da lactose. Constatou-se assim que a melhor levedura para a fermentação do permeado do soro de queijo é a Kluyveromyces Marxianus, estimando-se em 150 mg a produção de etanol por L de soro.
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Over the last two decades the research and development of legged locomotion robots has grown steadily. Legged systems present major advantages when compared with ‘traditional’ vehicles, because they allow locomotion in inaccessible terrain to vehicles with wheels and tracks. However, the robustness of legged robots, and especially their energy consumption, among other aspects, still lag behind mechanisms that use wheels and tracks. Therefore, in the present state of development, there are several aspects that need to be improved and optimized. Keeping these ideas in mind, this paper presents the review of the literature of different methods adopted for the optimization of the structure and locomotion gaits of walking robots. Among the distinct possible strategies often used for these tasks are referred approaches such as the mimicking of biological animals, the use of evolutionary schemes to find the optimal parameters and structures, the adoption of sound mechanical design rules, and the optimization of power-based indexes.
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Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.
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The present work describes the optimization of a short-term assay, based on the inhibition of the esterase activity of the alga Pseudokirchneriella subcapitata, in a microplate format. The optimization of the staining procedure showed that the incubation of the algal cells with 20 μmolL−1 fluorescein diacetate (FDA) for 40 min allowed discrimination between metabolic active and inactive cells. The shortterm assay was tested using Cu as toxicant. For this purpose, algal cells, in the exponential or stationary phase of growth, were exposed to the heavy metal in growing conditions. After 3 or 6 h, cells were subsequently stained with FDA, using the optimized procedure. For Cu, the 3- and 6-h EC50 values, based on the inhibition of the esterase activity of algal cells in the exponential phase of growth, were 209 and 130 μg L−1, respectively. P. subcapitata cells, in the stationary phase of growth, displayed higher effective concentration values than those observed in the exponential phase. The 3- and 6-h EC50 values for Cu, for cells in the stationary phase, were 443 and 268 μgL−1, respectively. This short-term microplate assay showed to be a rapid endpoint for testing toxicity using the alga P. subcapitata. The small volume required, the simplicity of the assay (no washing steps), and the automatic reading of the fluorescence make the assay particularly well suited for the evaluation of the toxicity of a high number of environmental samples.
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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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It is generally challenging to determine end-to-end delays of applications for maximizing the aggregate system utility subject to timing constraints. Many practical approaches suggest the use of intermediate deadline of tasks in order to control and upper-bound their end-to-end delays. This paper proposes a unified framework for different time-sensitive, global optimization problems, and solves them in a distributed manner using Lagrangian duality. The framework uses global viewpoints to assign intermediate deadlines, taking resource contention among tasks into consideration. For soft real-time tasks, the proposed framework effectively addresses the deadline assignment problem while maximizing the aggregate quality of service. For hard real-time tasks, we show that existing heuristic solutions to the deadline assignment problem can be incorporated into the proposed framework, enriching their mathematical interpretation.
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Constrained nonlinear optimization problems are usually solved using penalty or barrier methods combined with unconstrained optimization methods. Another alternative used to solve constrained nonlinear optimization problems is the lters method. Filters method, introduced by Fletcher and Ley er in 2002, have been widely used in several areas of constrained nonlinear optimization. These methods treat optimization problem as bi-objective attempts to minimize the objective function and a continuous function that aggregates the constraint violation functions. Audet and Dennis have presented the rst lters method for derivative-free nonlinear programming, based on pattern search methods. Motivated by this work we have de- veloped a new direct search method, based on simplex methods, for general constrained optimization, that combines the features of the simplex method and lters method. This work presents a new variant of these methods which combines the lters method with other direct search methods and are proposed some alternatives to aggregate the constraint violation functions.
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Joining of components with structural adhesives is currently one of the most widespread techniques for advanced structures (e.g., aerospace or aeronautical). Adhesive bonding does not involve drilling operations and it distributes the load over a larger area than mechanical joints. However, peak stresses tend to develop near the overlap edges because of differential straining of the adherends and load asymmetry. As a result, premature failures can be expected, especially for brittle adhesives. Moreover, bonded joints are very sensitive to the surface treatment of the material, service temperature, humidity and ageing. To surpass these limitations, the combination of adhesive bonding with spot-welding is a choice to be considered, adding a few advantages like superior static strength and stiffness, higher peeling and fatigue strength and easier fabrication, as fixtures during the adhesive curing are not needed. The experimental and numerical study presented here evaluates hybrid spot-welded/bonded single-lap joints in comparison with the purely spot-welded and bonded equivalents. A parametric study on the overlap length (LO) allowed achieving different strength advantages, up to 58% compared to spot-welded joints and 24% over bonded joints. The Finite Element Method (FEM) and Cohesive Zone Models (CZM) for damage growth were also tested in Abaqus® to evaluate this technique for strength prediction, showing accurate estimations for all kinds of joints.
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With the increasing complexity of current networks, it became evident the need for Self-Organizing Networks (SON), which aims to automate most of the associated radio planning and optimization tasks. Within SON, this paper aims to optimize the Neighbour Cell List (NCL) for Long Term Evolution (LTE) evolved NodeBs (eNBs). An algorithm composed by three decisions were were developed: distance-based, Radio Frequency (RF) measurement-based and Handover (HO) stats-based. The distance-based decision, proposes a new NCL taking account the eNB location and interference tiers, based in the quadrants method. The last two algorithms consider signal strength measurements and HO statistics, respectively; they also define a ranking to each eNB and neighbour relation addition/removal based on user defined constraints. The algorithms were developed and implemented over an already existent radio network optimization professional tool. Several case studies were produced using real data from a Portuguese LTE mobile operator. © 2014 IEEE.
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The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms have been investigated in the last years. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms. In this case the trajectory planning is formulated as an optimization problem with constraints.