On the use of particle swarm optimization to maximize bending stiffness of functionally graded structures

Functionally graded materials are a type of composite materials which are tailored to provide continuously varying properties, according to specific constituent's mixing distributions. These materials are known to provide superior thermal and mechanical performances when compared to the traditional laminated composites, because of this continuous properties variation characteristic, which enables among other advantages, smoother stresses distribution profiles. Therefore the growing trend on the use of these materials brings together the interest and the need for getting optimum configurations concerning to each specific application. In this work it is studied the use of particle swarm optimization technique for the maximization of a functionally graded sandwich beam bending stiffness. For this purpose, a set of case studies is analyzed, in order to enable to understand in a detailed way, how the different optimization parameters tuning can influence the whole process. It is also considered a re-initialization strategy, which is not a common approach in particle swarm optimization as far as it was possible to conclude from the published research works. As it will be shown, this strategy can provide good results and also present some advantages in some conditions. This work was developed and programmed on symbolic computation platform Maple 14. (C) 2013 Elsevier B.V. All rights reserved.

Hyperspectral unmixing based on mixtures of Dirichlet components

This paper introduces a new unsupervised hyperspectral unmixing method conceived to linear but highly mixed hyperspectral data sets, in which the simplex of minimum volume, usually estimated by the purely geometrically based algorithms, is far way from the true simplex associated with the endmembers. The proposed method, an extension of our previous studies, resorts to the statistical framework. The abundance fraction prior is a mixture of Dirichlet densities, thus automatically enforcing the constraints on the abundance fractions imposed by the acquisition process, namely, nonnegativity and sum-to-one. A cyclic minimization algorithm is developed where the following are observed: 1) The number of Dirichlet modes is inferred based on the minimum description length principle; 2) a generalized expectation maximization algorithm is derived to infer the model parameters; and 3) a sequence of augmented Lagrangian-based optimizations is used to compute the signatures of the endmembers. Experiments on simulated and real data are presented to show the effectiveness of the proposed algorithm in unmixing problems beyond the reach of the geometrically based state-of-the-art competitors.

Machine learning Vasicek model calibration with Gaussian processes

In this article, we calibrate the Vasicek interest rate model under the risk neutral measure by learning the model parameters using Gaussian processes for machine learning regression. The calibration is done by maximizing the likelihood of zero coupon bond log prices, using mean and covariance functions computed analytically, as well as likelihood derivatives with respect to the parameters. The maximization method used is the conjugate gradients. The only prices needed for calibration are zero coupon bond prices and the parameters are directly obtained in the arbitrage free risk neutral measure.

Optimal design for active damping in sandwich structures using the Direct MultiSearch method

This paper addresses the problem of optimal positioning of surface bonded piezoelectric patches in sandwich plates with viscoelastic core and laminated face layers. The objective is to maximize a set of modal loss factors for a given frequency range using multiobjective topology optimization. Active damping is introduced through co-located negative velocity feedback control. The multiobjective topology optimization problem is solved using the Direct MultiSearch Method. An application to a simply supported sandwich plate is presented with results for the maximization of the first six modal loss factors. The influence of the finite element mesh is analyzed and the results are, to some extent, compared with those obtained using alternative single objective optimization.

Maximização da valorização energética em aterros sanitários recorrendo a equipamentos baseados no Ciclo Orgânico de Rankine (ORC)

Atualmente, os aterros sanitários representam uma solução para a gestão e tratamento dos resíduos sólidos urbanos. Da deposição, ocorrem duas formas de emissões ao longo do tempo, a produção de biogás e de lixiviados, que resultam sobretudo da decomposição da matéria orgânica. Um dos principais constituintes do biogás é o metano, o qual tem elevado poder calorífico. O presente trabalho aborda, a maximização da valorização energética em aterros sanitários, recorrendo a equipamentos baseados no Ciclo Orgânico de Rankine (ORC) para a produção de eletricidade. É apresentado como caso de estudo a central de valorização energética da Suldouro, em Sermonde, que produz eletricidade a partir do biogás resultante da decomposição da matéria orgânica depositada em aterro. O biogás é utilizado como combustível para os motogeradores utilizados para o seu aproveitamento energético, sendo que apenas cerca de 40% do potencial energético contido no biogás é transformado em eletricidade, registando-se perdas sobretudo nas emissões dos gases de exaustão e na água de arrefecimento dos motores. Para avaliação do potencial da recuperação energética dos gases de escape é avaliado o desempenho termodinâmico do ciclo ORC. Para tal foi desenvolvida uma ferramenta em MATLAB utilizando como modelo a configuração do ORC com recuperador de calor. O cálculo das propriedades termodinâmicas dos fluidos foi obtido através da criação de uma sub-rotina que chama o programa CoolProp. Este programa restitui propriedades como a entalpia, entropia, pressões e temperaturas em cada ponto do ciclo, permitindo assim ao utilizador otimizar o tempo na obtenção de resultados. A avaliação económica é fundamental na tomada de decisões por parte do investidor e dos financiadores do projeto. É então apresentada a análise económica e efetuada uma análise de sensibilidade, onde foram efetuadas variações nos vetores mais importantes de forma a poder avaliar-se o impacto em termos da sua rentabilidade. A ferramenta desenvolvida permite obter de forma prática, os três indicadores económicos extremamente influentes no que se refere à tomada de decisão. A utilização dos sistemas ORC e os seus benefícios não se esgotam na maximização dos aproveitamentos da valorização energética em aterros sanitários. Também a recuperação de calor para a produção de energia elétrica pode ter um impacto importante em muitos setores intensivos de energia, contribuindo significativamente para a redução do consumo e aumentando a eficiência de todo o processo de produção.

Influence of reconstruction parameters for FBP in semiquantification of brain studies with 123I-FPCIT

Brain dopamine transporters imaging by Single Photon Emission Tomography (SPECT) with 123I-FP-CIT has become an important tool in the diagnosis and evaluation of parkinsonian syndromes, since this radiopharmaceutical exhibits high affinity for membrane transporters responsible for cellular reabsorption of dopamine on the striatum. However, Ordered Subset Expectation Maximization (OSEM) is the method recommended in the literature for imaging reconstruction. Filtered Back Projection (FBP) is still used due to its fast processing, even if it presents some disadvantages. The aim of this work is to investigate the influence of reconstruction parameters for FBP in semiquantification of Brain Studies with 123I-FPCIT compared with those obtained with OSEM recommended reconstruction.

Gestão integrada de ativos num contexto real

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Manutenção

Influência dos parâmetros de reconstrução por retroprojeção filtrada na semiquantificação em estudos cerebrais com 123I-FPCIT

A imagem de transportadores cerebrais da dopamina com recurso à tomografia por emissão de fotão único com 123I-FP-CIT tornou-se uma ferramenta importante no diagnóstico e avaliação de síndromes parkinsonianos. Embora o algoritmo de reconstrução de imagem Ordered Subset Expectation Maximization (OSEM) seja o método mais recomendado na literatura para reconstrução da imagem, o Filtered Back Projection (FBP) é ainda usado devido à sua rapidez. O objetivo deste trabalho é investigar a influência dos parâmetros de reconstrução para FBP na semiquantificação em estudos cerebrais com 123I-FPCIT em comparação com os obtidos com a reconstrução recomendada por OSEM.

Design of New Materials for Passive Vibration Control

The objective of this contribution is to extend the models of cellular/composite material design to nonlinear material behaviour and apply them for design of materials for passive vibration control. As a first step a computational tool allowing determination of optimised one-dimensional isolator behaviour was developed. This model can serve as a representation for idealised macroscopic behaviour. Optimal isolator behaviour to a given set of loads is obtained by generic probabilistic metaalgorithm, simulated annealing. Cost functional involves minimization of maximum response amplitude in a set of predefined time intervals and maximization of total energy absorbed in the first loop. Dependence of the global optimum on several combinations of leading parameters of the simulated annealing procedure, like neighbourhood definition and annealing schedule, is also studied and analyzed. Obtained results facilitate the design of elastomeric cellular materials with improved behaviour in terms of dynamic stiffness for passive vibration control.

A hierarquia dos determinantes da estrutura de capital em empresas portuguesas

Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Contabilidade e Finanças, sob orientação de Adalmiro Álvaro Malheiro de Castro Andrade Pereira

Dificuldades encontradas no processo de internacionalização: estudo nas PME de mobiliário nos concelhos de Paços de Ferreira e Paredes

Dissertação de Mestrado apresentada ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Auditoria, sob orientação do Mestre Adalmiro Álvaro Malheiro de Castro Andrade Pereira

Negotiation mechanism for self-organized scheduling system with collective intelligence

Current Manufacturing Systems challenges due to international economic crisis, market globalization and e-business trends, incites the development of intelligent systems to support decision making, which allows managers to concentrate on high-level tasks management while improving decision response and effectiveness towards manufacturing agility. This paper presents a novel negotiation mechanism for dynamic scheduling based on social and collective intelligence. Under the proposed negotiation mechanism, agents must interact and collaborate in order to improve the global schedule. Swarm Intelligence (SI) is considered a general aggregation term for several computational techniques, which use ideas and inspiration from the social behaviors of insects and other biological systems. This work is primarily concerned with negotiation, where multiple self-interested agents can reach agreement over the exchange of operations on competitive resources. Experimental analysis was performed in order to validate the influence of negotiation mechanism in the system performance and the SI technique. Empirical results and statistical evidence illustrate that the negotiation mechanism influence significantly the overall system performance and the effectiveness of Artificial Bee Colony for makespan minimization and on the machine occupation maximization.

Otimização de placas compósitas laminadas utilizando redes neuronais e enxames de partículas

Trabalho Final de mestrado para obtenção do grau de Mestre em engenharia Mecância

Multiobjective optimization of viscoelastic laminated sandwich structures using the Direct MultiSearch method

A multiobjective approach for optimization of passive damping for vibration reduction in sandwich structures is presented in this paper. Constrained optimization is conducted for maximization of modal loss factors and minimization of weight of sandwich beams and plates with elastic laminated constraining layers and a viscoelastic core, with layer thickness and material and laminate layer ply orientation angles as design variables. The problem is solved using the Direct MultiSearch (DMS) solver for derivative-free multiobjective optimization and solutions are compared with alternative ones obtained using genetic algorithms.

Strap repairs using embedded patches: numerical analysis and experimental results

Adhesively bonded repairs offer an attractive option for repair of aluminium structures, compared to more traditional methods such as fastening or welding. The single-strap (SS) and double-strap (DS) repairs are very straightforward to execute but stresses in the adhesive layer peak at the overlap ends. The DS repair requires both sides of the damaged structures to be reachable for repair, which is often not possible. In strap repairs, with the patches bonded at the outer surfaces, some limitations emerge such as the weight, aerodynamics and aesthetics. To minimize these effects, SS and DS repairs with embedded patches were evaluated in this work, such that the patches are flush with the adherends. For this purpose, in this work standard SS and DS repairs, and also with the patches embedded in the adherends, were tested under tension to allow the optimization of some repair variables such as the overlap length (LO) and type of adhesive, thus allowing the maximization of the repair strength. The effect of embedding the patch/patches on the fracture modes and failure loads was compared with finite elements (FE) analysis. The FE analysis was performed in ABAQUS® and cohesive zone modelling was used for the simulation of damage onset and growth in the adhesive layer. The comparison with the test data revealed an accurate prediction for all kinds of joints and provided some principles regarding this technique.