La thèse est relative à la compréhension de la physique et au contrôle des émissions acoustiques dans les jets turbulents simples et double-flux. La génération du bruit est associé à des structures turbulentes de grandes tailles caractéristiques et à la turbulence de petites échelles. i Il est maintenant admis que les structures de grandes échelles sont des instabilités se propageant dans un champ moyen turbulent. Ici elle sont analysées sur la base de la théorie linéaire non locale appelées PSE pour Parabolized Stability Equations. Ces instabilités inflexionnelles associées à la présence de couche de cisaillement sont des modes de Kelvin-Helmhotz. Dans le cas du jet sous détentu des cellules de choc apparaissent et influencent très fortement les taux d'amplification et fréquences des modes propres. Divers écoulements sont investigués, de faible nombre de Mach au jet double-flux supersonique dont le champ moyen provient de simulation LES (Cerfacs). Le champ acoustique lointain est déterminé par l'analogie de Ffowcs-Williams-Hawkings. Ensuite une étude de sensibilité originales des instabilités et du bruits par rapport à divers forage locaux est produite sur la base deséquations de stabilité PSE adjointes. Les fortes sensibilités apparaissent dans les couches de cisaillements et aussi dans une moindre mesure autour des cellules de chocs. Les sensibilités sont plus complexes pour le jet double flux et dépendent du mode instable étudié lié soit au jet primaire soit au jet secondaire. Les sensibilités maximales se trouvent auvoisinage de la sortie de la tuyère et à la limite ou à l’extérieur du cne potentiel. En complément une étudesur le jet simple flux permet de mettre en rapport les approches de quantification d'incertitude et la sensibilité calculée par des équations adjointes. Les résultats de sensibilité vont permettre de contribuer à proposer des stratégies de contrôle aero-acoustique dans les jets de turboréacteurs. / This thesis leads to a better knowledge of the physic and of the control of acoustic radiation in turbulent single and dual-stream jets.It is known that jet noise is produced by the turbulence present in the jet that can be separated in large coherent structures and fine structures. It is also concluded that these large-scale coherent structures are the instability waves of the jet and can be modelled as the flow field generated by the evolution of instability waves in a given turbulent jet. The growth rate and the streamwise wavenumber of a disturbance with a fixed frequency and azimuthal wavenumber are obtained by solving the non-local approach called Parabolized Stability Equations (PSE). Typically the Kelvin-Helmholtz instability owes its origin into the shear layer of the flow and, moreover, the inflection points of the mean velocity profile has a crucial importance in the instability of such a flow. The problem is more complex in case of imperfectly expanded jet where shock-cells manifest inside the jet and strongly interaction with the instability waves has been observed. Several configurations are tested in this thesis, from a subsonic incompressible case to the dual-stream underexpanded supersonic jet obtained by solving Large Eddy Simulations LES (CERFACS). The acoustic far-field is determined by the Ffowcs-Williams-Hawkings acoustic analogy. Then a sensitivity analysis of the jet with respect to external forcing acting in a localized region of the flow are investigated by solving the adjoint PSE equations. High sensitivity appeared in the shear-layer of the flow showing, also, a high dependency in the streamwise and radial direction. In the case of dual-stream jet the propagation of the instability in the inner and outer shear layer should be taken into account. This configuration leads to two different distinct Klevin-Helmholtz modes that are computed separately. The highest sensitivity is determined in the exit of the nozzle outside of the potential core of the jet. In addition, comparison between sensitivity computed by adjoint equations and Uncertainty Quantification (UQ) methods has been done, in the case of a single-stream jet, showing a link between these two methods for small variations of the input parameters. This result leads to the application of a lower cost tool for mathematical analysis of complex problem of industrial interest. This work and in particular the sensitivity theory investigated in this thesis contribute to a development of a new noise control strategy for aircraft jet.

This work discusses about issues of investment decision, which is crucial for every business. The aim of this thesis was to evaluate the effectiveness of selected investment project. To assess the potential of this investment, was necessary to assess the current status, whether the enterprise has enough resources to finance this intensive investment. Whether the project is not associated with an increase in the financial risk of the company. Then were identified revenues and expeditures of the project.It was finally in the evaluation of the effectiveness of investments carried out an analysis of the risk of the project.

Orientador: Prof. Dr. Edmarcio Antonio Belati / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, 2016. / A inclusão de fontes de geração distribuída (GD) em sistemas elétricos vem crescendo nos últimos anos motivando o uso de fontes de energia alternativas renováveis ao mesmo tempo em que tem aumentado a demanda de energia global. Uma das fontes que tem crescido nos últimos anos ao nível mundial é a energia eólica. Frente à possibilidade de uma situação de escassez de energia elétrica, o aumento no custo da eletricidade e a busca constante das companhias por ter uma operação econômica do sistema elétrico, o estudo do desempenho ótimo da rede é apresentado como um tema importante para os centros de operação das companhias de energia elétrica. Desta forma, os Sistemas Elétricos de Potência (SEP) necessitam de ferramentas rápidas de análise para auxiliar os agentes na tomada de decisões surgindo assim o interesse em desenvolver ferramentas de análise que permitam aos operadores da rede tomarem decisões rápidas em relação às possíveis eventualidades ou variações no comportamento do sistema. O objetivo principal deste trabalho é aplicar análise de sensibilidade de segunda ordem (ASSO) nos sistemas de distribuição com geração eólica para obter um possível ponto de operação ótima de forma rápida após ocorrerem perturbações tanto na geração eólica quanto na carga do sistema. Para tanto foi modelado um Fluxo de Potência Ótimo (FPO) com as características do sistema e com o objetivo de minimizar as perdas de potência ativa, caracterizando assim o caso base (CB) e posteriormente aplicou-se a ASSO à solução encontrada no CB de forma a obter uma resposta rápida e econômica. Vale destacar que para validação da metodologia proposta buscou-se aplica-lo em sistemas de distribuição de energia elétrica. / The inclusion of distributed generation sources (DG) in electrical systems has been growing in recent years encouraging the use of alternative renewable energy sources at the same time it has increased the global energy demand. One of the sources that has grown in recent years worldwide is wind energy. Facing the possibility of energy shortage situation, the increase in the cost of electricity and the constant pursuit of companies to have an economic operation of the electrical system, the study of the network optimal performance is presented as a major issue for the operation centers of electricity companies. Thus, the Electric Power System (EPS) need fast analysis tools to assist agents in decision-making thus resulting interest in developing analysis tools that allow network operators to make quick decisions in relation to the possible eventualities or variations in system behavior. The main objective of this work is to apply analysis of second-order sensitivity (ASOS) in distribution systems with wind generation for an approximate point of optimal operation fastest as possible after disturbances occur both in wind generation, as the system load. For Optimal Power Flow (OPF) with the system's features and with the objective of minimize the loss of active power much was modeled, characterizing the base case (BC) and then applying the ASOS the solution obtained in BC in order to get a quick answer and economic. Note that to validate the proposed methodology we sought to apply it in electric power distribution systems.

abstract: Bank institutions employ several marketing strategies to maximize new customer acquisition as well as current customer retention. Telemarketing is one such approach taken where individual customers are contacted by bank representatives with offers. These telemarketing strategies can be improved in combination with data mining techniques that allow predictability of customer information and interests. In this thesis, bank telemarketing data from a Portuguese banking institution were analyzed to determine predictability of several client demographic and financial attributes and find most contributing factors in each. Data were preprocessed to ensure quality, and then data mining models were generated for the attributes with logistic regression, support vector machine (SVM) and random forest using Orange as the data mining tool. Results were analyzed using precision, recall and F1 score. / Dissertation/Thesis / Masters Thesis Computer Science 2016

abstract: Researchers who conduct longitudinal studies are inherently interested in studying individual and population changes over time (e.g., mathematics achievement, subjective well-being). To answer such research questions, models of change (e.g., growth models) make the assumption of longitudinal measurement invariance. In many applied situations, key constructs are measured by a collection of ordered-categorical indicators (e.g., Likert scale items). To evaluate longitudinal measurement invariance with ordered-categorical indicators, a set of hierarchical models can be sequentially tested and compared. If the statistical tests of measurement invariance fail to be supported for one of the models, it is useful to have a method with which to gauge the practical significance of the differences in measurement model parameters over time. Drawing on studies of latent growth models and second-order latent growth models with continuous indicators (e.g., Kim & Willson, 2014a; 2014b; Leite, 2007; Wirth, 2008), this study examined the performance of a potential sensitivity analysis to gauge the practical significance of violations of longitudinal measurement invariance for ordered-categorical indicators using second-order latent growth models. The change in the estimate of the second-order growth parameters following the addition of an incorrect level of measurement invariance constraints at the first-order level was used as an effect size for measurement non-invariance. This study investigated how sensitive the proposed sensitivity analysis was to different locations of non-invariance (i.e., non-invariance in the factor loadings, the thresholds, and the unique factor variances) given a sufficient sample size. This study also examined whether the sensitivity of the proposed sensitivity analysis depended on a number of other factors including the magnitude of non-invariance, the number of non-invariant indicators, the number of non-invariant occasions, and the number of response categories in the indicators. / Dissertation/Thesis / Doctoral Dissertation Psychology 2016

abstract: City administrators and real-estate developers have been setting up rather aggressive energy efficiency targets. This, in turn, has led the building science research groups across the globe to focus on urban scale building performance studies and level of abstraction associated with the simulations of the same. The increasing maturity of the stakeholders towards energy efficiency and creating comfortable working environment has led researchers to develop methodologies and tools for addressing the policy driven interventions whether it’s urban level energy systems, buildings’ operational optimization or retrofit guidelines. Typically, these large-scale simulations are carried out by grouping buildings based on their design similarities i.e. standardization of the buildings. Such an approach does not necessarily lead to potential working inputs which can make decision-making effective. To address this, a novel approach is proposed in the present study. The principle objective of this study is to propose, to define and evaluate the methodology to utilize machine learning algorithms in defining representative building archetypes for the Stock-level Building Energy Modeling (SBEM) which are based on operational parameter database. The study uses “Phoenix- climate” based CBECS-2012 survey microdata for analysis and validation. Using the database, parameter correlations are studied to understand the relation between input parameters and the energy performance. Contrary to precedence, the study establishes that the energy performance is better explained by the non-linear models. The non-linear behavior is explained by advanced learning algorithms. Based on these algorithms, the buildings at study are grouped into meaningful clusters. The cluster “mediod” (statistically the centroid, meaning building that can be represented as the centroid of the cluster) are established statistically to identify the level of abstraction that is acceptable for the whole building energy simulations and post that the retrofit decision-making. Further, the methodology is validated by conducting Monte-Carlo simulations on 13 key input simulation parameters. The sensitivity analysis of these 13 parameters is utilized to identify the optimum retrofits. From the sample analysis, the envelope parameters are found to be more sensitive towards the EUI of the building and thus retrofit packages should also be directed to maximize the energy usage reduction. / Dissertation/Thesis / Masters Thesis Architecture 2017

Made available in DSpace on 2016-12-08T17:19:19Z (GMT). No. of bitstreams: 1 Joanesson S Schmidt.pdf: 1440856 bytes, checksum: df26cfcda5fb5443496a9daa2e65e4e6 (MD5) Previous issue date: 2013-02-18 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In structural optimization problems based on derivatives the calculation of the displacements sensitivity with respect to design variables is a critical step. Accurate, stable and efficient methods of sensitivity analysis are sought. The occurrence of errors during the calculation of sensitivity motivates a significant research and this paper presents a way to eliminate the errors that arise when using the semi-analytical displacements sensitivity analysis with respect to shape variables in rigid rotation dominated problems. A finite element formulation for structures modelled with bar elements is developed and the complex variable semi-analytical method is implemented in order to apply to problems with geometric nonlinearity. The sensitivity of the displacements is performed with respect to material and shape parameters and the complex variables semi-analytic method is compared to other classical methods of sensitivity analysis: the finite difference method and real variables semi-analytical method. The comparison is performed using two examples known in the literature for presenting geometric nonlinearity. / Em problemas estruturais de otimização baseados em derivada, o cálculo da sensibilidade dos deslocamentos em relação às variáveis de projeto é uma etapa fundamental. Buscam-se métodos de análise de sensibilidade que sejam precisos, estáveis e eficientes. O aparecimento de erros durante o cálculo da sensibilidade motiva uma pesquisa significativa e o presente trabalho aborda uma forma de eliminar os erros que surgem ao se utilizar o método semianalítico na análise de sensibilidade dos deslocamentos em relação a variáveis de projetos de forma em problemas dominados por rotação rígida. Uma formulação de elementos finitos para estruturas modeladas com elementos de barra é desenvolvida e o método de análise de sensibilidade semi-analítico com variáveis complexas é implementado visando a aplicação em problemas com não-linearidade geométrica. A sensibilidade dos deslocamentos é realizada em relação a parâmetros materiais e de forma e o método semi-analítico com variáveis complexas é comparado com outros métodos clássicos de análise de sensibilidade: método das diferenças finitas e método semi-analítico com variáveis reais. A comparação é realizada através de dois exemplos que são conhecidos na literatura por apresentar não linearidade geométrica.

Made available in DSpace on 2016-12-08T17:19:33Z (GMT). No. of bitstreams: 1 Capa.pdf: 100296 bytes, checksum: 85da33d7d5aa32b41734416b7ba82f1a (MD5) Previous issue date: 2009-09-16 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Numerical simulation of metal forming processes requires a constitutive model, which depends upon adequate material parameters. A direct determination of material parameters usually admits homogeneous stress and strain states in the specimen, thereby narrowing the application range to moderate deformations or even compromising accuracy in some industrial applications. Therefore, a combined experimental and numerical technique based on optimisation strategies is recommended. Such method is generally known as parameter identification and produces stress states close to those to be verified in industrial operations. In this work, a parameter identification technique based upon deep drawing experiments is presented. Sensitivity analysis is performed using a modified finite difference method, and the optimization itself is developed using quadratic programming. Sensitivity results using the classical and the modified finite difference methods are studied and compared, especially with respect to the application of automatic or imposed step increments. It is observed that the modified method yields a more effective behaviour with respect to the automatic time step strategy, allowing use of a wider range of penalization factors and attaining greater efficiency. Several identification problems are presented showing qualitative agreement with related research in the literature. Difficulties arise in the simultaneous determination of multiple material parameters, due to typical flat regions or to the presence of local minima in the design space, suggesting future combination of the presented approach with evolutionary algorithms. / Toda simulação numérica de um processo de conformação mecânica requer um modelo constitutivo, que depende de parâmetros materiais adequados. Muitas vezes a determinação direta dos parâmetros materiais admite um estado homogêneo de tensão e deformação no corpo de prova, provocando um estreitamento na sua faixa de aplicação as situações onde ocorrem deformações moderadas ou então comprometendo a precisão dos resultados em algumas aplicações industriais. Portanto, uma combinação entre as técnicas numérica e experimental utilizando técnicas de otimização é recomendada. Esta estratégia é geralmente conhecida como identificação de parâmetros e produz estados de tensão próximos ao verificado nas operações industriais. Neste trabalho é apresentada a técnica de identificação de parâmetros baseado num processo de estampagem profunda. A análise de sensibilidade é avaliada utilizando um método de diferenças finitas modificado e o processo de otimização utiliza programação quadrática seqüencial. Estudam-se os resultados de análise de sensibilidade utilizando os métodos de diferenças finitas tradicional e modificado, sujeitos a incrementos de tempo automático e imposto. Observa-se que a aplicação do método modificado fornece maior eficácia na aplicação da estratégia de incremento de tempo automática, além de permitir o uso de uma faixa mais ampla de fatores de penalização para o contato e de resultar em maior eficiência numérica. Vários problemas de identificação são apresentados, mostrando concordância qualitativa com os resultados disponíveis em publicações da literatura correlata. Dificuldades são encontradas na determinação simultânea de vários parâmetros devido à presença de regiões planas ou de mínimos locais no espaço de projeto, sugerindo a futura combinação da abordagem proposta neste trabalho com algoritmos evolucionários.

The topic of this thesis is the evaluation of risk in enterprise. First section summarizes common knowledge related to investment process and states methods used for analysis of risk and investments efficiency. Second part evaluates economic efficiency and risk of a future investments in the particular enterprise. Projects are critical to the realization of performing organization's strategies. Each project contains some degree of risk and it is required to be aware of these risks and to develop the necessary responses to get the desired level of project success. Because projects' risks are multidimensional, they must be evaluated by using risk evaluation methods. The aim of this part is to provide an analytic tool to evaluate the project risks. At first the thesis analysis net present value and other investment criteria of the construction project without risk factors. Subsequently the projects' risks are are evaluated by using risk premium. To study of how projected performance varies along with changes in the key assumptions on which the projections are based is used the sensitivity analysis. The main sources for data was the enterprise environment.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-08-05T14:27:22Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_.pdf: 1522093 bytes, checksum: bb2928d81ecdfb4d866a999cf07f0b76 (MD5) / Made available in DSpace on 2016-08-05T14:27:22Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_.pdf: 1522093 bytes, checksum: bb2928d81ecdfb4d866a999cf07f0b76 (MD5) Previous issue date: 2016-02-29 / CNPq / A escolha de uma estratégia adequada de manutenção para os sistemas produtivos de uma organização é um pré-requisito para a sua efetividade. Destaca-se que esta escolha é um processo decisório que utiliza modelos matemáticos para encontrar uma estratégia que otimize a relação custo-benefício das ações de manutenção. Tal estratégia deve levar em conta períodos para a execução das intervenções, bem como a existência de metas de produção. Embora seja comum a inclusão de paradas para manutenção entre períodos de operações dos sistemas nos planos de produção, geralmente aqueles modelos ignoram a finitude da duração de tais paradas; o mesmo acontece com relação à escassez dos recursos de manutenção. Entretanto, esses fatores restringem a quantidade de ações que podem ser executadas a cada parada e, portanto, não devem ser desprezados. Em virtude disso, é necessário identificar, dentre as ações de manutenção passíveis de serem executadas no sistema, aquelas que são críticas para seu(s) indicador(es) de performance. Isso é uma prerrogativa dos modelos de manutenção seletiva. Não obstante, a resolução desses modelos é tarefa árdua, já que problemas combinatórios necessitam de métodos heurísticos para serem solucionados. Neste trabalho, ambas as necessidades foram trabalhadas. O fim principal da investigação foi contribuir com os modelos de manutenção seletiva dedicados a sistemas orientados a múltiplas missões. Para isso, expandiu-se um modelo de manutenção seletiva voltado a sistemas orientados a multimissões e desenvolveu-se um algoritmo genético para resolver o problema. Estes foram postos à prova em uma aplicação numérica. Atestados a efetividade do método e a aplicabilidade do modelo, fez-se análises de sensibilidade e formulou-se modelos alternativos. Ainda se fez recomendações para a canalização de esforços em trabalhos futuros. No todo, a pesquisa configura-se como tendo natureza básica e aplicada, bem como caráter explicativo. Quanto à abordagem, é quantitativa e utiliza o método da modelagem e simulação. / The choice of a suitable maintenance strategy for productive systems of an organization is a requirement for its effectiveness. It is emphasized that this choice is a decision-making process that uses mathematical models to find a strategy that optimizes the cost-effectiveness of maintenance actions. This strategy must take into account periods for the implementation of assistance, as well as the existence of production goals. Although it is common to include maintenance downtime between periods of systems operations in production schedules, generally those models ignore the finite length of these stops; the same applies regarding to the shortage of maintenance resources. However, these factors constrain the number of actions that can be performed at each break and, therefore, should not be neglected. As a result, it is necessary to identify, among the maintenance actions that can be performed on the system, those that are critical to the performance indicator(s). This is a prerogative of selective maintenance models. Nevertheless, the resolution of these models is a difficult task, as combinatorial problems require heuristic methods to be solved. In this work, both requirements were addressed. The main purpose of the research was to contribute to the selective maintenance models dedicated to multiple mission’s oriented systems. For this it has been expanded a multiple mission oriented maintenance model and was developed a genetic algorithm for solving the problem. These were tested in a numerical application. Attested the effectiveness of the method and the applicability of the model, a sensitivity analysis were performed and alternative models were developed. Still it has made recommendations for concentrating efforts in future work. Overall, the research is characterized as having basic and applied nature, as well as explanatory character. As for the approach, it is quantitative and uses the modeling and simulation method.