No description available.

No description available.

No description available.

[Truncated abstract] Centrifugal pumps are the most prevalent, electrically powered rotating machines used today. Each pump is designed to deliver fluid of a given flow rate at a certain pressure. The point at which electrical energy is converted most efficiently into increased pressure is known as the Best Efficiency Point. For a variety of reasons, pumps often operate away from this point (intentionally or otherwise), which not only reduces efficiency, but also increases the likelihood of premature component failure. Acoustic emissions (AE) are high frequency elastic waves, in the range of 20-2000kHz, released when a material undergoes localised plastic deformation. Acoustic emission testing is the process of measuring and analysing these stress waves in an attempt to diagnose the nature and severity of the underlying fault. AE sensors mounted on the surface of a machine or structure also detect any stress waves generated within the fluid being transmitted through to the structure. Unfortunately, attempts to detect incipient component faults in centrifugal pumps using acoustic emission analysis have been complicated by the sensitivity of AE to a pump?s operating state. Therefore, the aim of this thesis was to determine how acoustic emission monitoring could be used to identify the hydraulic conditions within a pump. Data was collected during performance tests from a variety of small end-suction pumps and from one much larger double-suction pump. A system was developed to collect, process and analyse any number of AE features (be they related to discrete AE events, or due to the continuous background AE level) from continuously operating equipment. ... Unfortunately, results from smaller pumps were less conclusive, particularly at low flows, probably due to the relatively small changes in hydraulic energy across the range of flows, and consequent sensitivity to the testing process. However, even in these pumps consistent patterns in hit energies were observed resulting in the conclusion that low to medium flows in centrifugal pumps are typified by a very large number of very low energy (VLE) events. These decrease in number and increase in energy as flow approaches BEP and/or is reduced to very low flows. High flows above BEP are marked by an absence of these VLE events, with bursts having significantly higher energies and spread over a much greater range. Unfortunately, these VLE events are too small to affect averaged trends, indicating that further work on a suitable filter is required. vi

abstract: Carbon Capture and Storage (CCS) is a climate stabilization strategy that prevents CO2 emissions from entering the atmosphere. Despite its benefits, impactful CCS projects require large investments in infrastructure, which could deter governments from implementing this strategy. In this sense, the development of innovative tools to support large-scale cost-efficient CCS deployment decisions is critical for climate change mitigation. This thesis proposes an improved mathematical formulation for the scalable infrastructure model for CCS (SimCCS), whose main objective is to design a minimum-cost pipe network to capture, transport, and store a target amount of CO2. Model decisions include source, reservoir, and pipe selection, as well as CO2 amounts to capture, store, and transport. By studying the SimCCS optimal solution and the subjacent network topology, new valid inequalities (VI) are proposed to strengthen the existing mathematical formulation. These constraints seek to improve the quality of the linear relaxation solutions in the branch and bound algorithm used to solve SimCCS. Each VI is explained with its intuitive description, mathematical structure and examples of resulting improvements. Further, all VIs are validated by assessing the impact of their elimination from the new formulation. The validated new formulation solves the 72-nodes Alberta problem up to 7 times faster than the original model. The upgraded model reduces the computation time required to solve SimCCS in 72% of randomly generated test instances, solving SimCCS up to 200 times faster. These formulations can be tested and then applied to enhance variants of the SimCCS and general fixed-charge network flow problems. Finally, an experience from testing a Benders decomposition approach for SimCCS is discussed and future scope of probable efficient solution-methods is outlined. / Dissertation/Thesis / Masters Thesis Industrial Engineering 2017

A relevância da infraestrutura de transporte para incrementos em produtividade, induzindo ao desenvolvimento socioeconômico de determinada região é amplamente reconhecida. O Brasil, no entanto, apresenta sérias deficiências em relação à sua infraestrutura de transporte, oriundas de seu desenvolvimento histórico e da redução de níveis de investimentos públicos no setor nas últimas décadas. Estas deficiências traduzem-se em grande concentração no modal rodoviário para o transporte de cargas, menos eficiente do que os modais ferroviário e hidroviário, resultando em reduzida competitividade das organizações nacionais. Neste contexto, objetivou-se no presente trabalho a proposição de um modelo para avaliação e seleção de investimentos em infraestrutura de transporte de cargas, considerando-se seu caráter multidimensional. Para isso, foi proposta metodologia integrando os conceitos de análise de decisão multicritério e de programação matemática, representados pela teoria de utilidade multiatributo (Multi-Attribute Utility Theory - MAUT) e por problema de otimização de fluxos em rede (Minimum Cost Network Flow Problem - MCNFP), respectivamente. No desenvolvimento do modelo foram contemplados critérios de avaliação referentes às dimensões de análise financeira, operacional e ambiental. Posteriormente, foi considerada a aplicação de versões do modelo proposto com diferentes números de períodos de análise em caso ilustrativo, representativo da rede de transporte disponível e planejada da região Norte do Brasil. A aplicação das diversas versões do modelo proposto, de forma geral, apresentou resultados compatíveis com as teorias relacionadas à avaliação deste problema de decisão, incluindo indução à multimodalidade. Algumas versões do modelo apresentaram violações em algumas de suas restrições. Estes resultados adversos não foram plenamente eliminados, devido a limitações das ferramentas adotadas para aplicação. No entanto, foi possível a correção manual destas violações, resultando em soluções viáveis que, apesar de não serem consideradas ótimas, são mais completas do que soluções obtidas por meio de metodologias unidimensionais de análise. Por fim, foram apresentadas recomendações para condução de trabalhos futuros visando eliminação dos resultados adversos do modelo proposto e complementação de sua análise. / The role of transport infrastructure in productivity increases leading to regional social-economic development is widely recognized. Brazil, however, has serious deficiencies in its transport infrastructure, rooted in the country\'s historical development and in the recent decades\' reduction of public investment in the sector. These deficiencies can be observed in Brazil\'s strong focus on roads for cargo transportation, which besides being less efficient than rail and waterways, results in reduced competitiveness of national enterprises. In this context, the aim of this work was to propose a model for evaluating and selecting investments in freight\'s transportation infrastructure, considering its multidimensional character. It was proposed a methodology integrating the concepts of multi-criteria decision analysis and mathematical programming, represented by the Multi-Attribute Utility Theory (MAUT) along with the Minimum Cost Network Flow Problem (MCNFP). The developed model included financial, operational and environmental analysis evaluation criteria. Subsequently, this study applied the proposed model into a case study of the transportation network, available and planned, of the Northern region of Brazil. Overall, the application of various versions of the proposed model yielded results consistent with related evaluation and decision making theories, including induction of multimodality. Some versions of the model presented some violations of its restrictions. These adverse results were not fully eliminated due to the limitations of the application tools utilized. It was possible, however, to manually correct these violations and obtain viable solutions that, while cannot be considered optimal, are more complete than those obtained by single dimension analysis. Finally, recommendations were made for future studies aiming at eliminating the proposed model\'s adverse outcomes, and complementing its analysis.

Past studies (primarily on steady state problems) that have compared the penalty and the velocity-pressure finite element formulations on a variety of problems have concluded that both methods yield solutions of comparable accuracy, and that the choice of one method over the other is dictated by which of the two is more efficient. In this work, we show that the penalty finite element method yields inaccurate solutions at large times on a class of transient problems, while the velocity-pressure formulation yields solutions that are in good agreement with the analytical solution. Numerical studies are conducted on various problems to compare these two formulations on the basis of rates of convergence, total number of equations to be solved and accuracy of results. We found that both formulations give almost the same rates of convergence in all problems, however the penalty formulation involves lesser number of equations than the velocity-pressure formulation due to implicit treatment of pressure field, and hence is more efficient. In some of the problems we have also compared a finite volume method with the penalty and velocity-pressure formulations on the basis of accuracy and computational cost.

A relevância da infraestrutura de transporte para incrementos em produtividade, induzindo ao desenvolvimento socioeconômico de determinada região é amplamente reconhecida. O Brasil, no entanto, apresenta sérias deficiências em relação à sua infraestrutura de transporte, oriundas de seu desenvolvimento histórico e da redução de níveis de investimentos públicos no setor nas últimas décadas. Estas deficiências traduzem-se em grande concentração no modal rodoviário para o transporte de cargas, menos eficiente do que os modais ferroviário e hidroviário, resultando em reduzida competitividade das organizações nacionais. Neste contexto, objetivou-se no presente trabalho a proposição de um modelo para avaliação e seleção de investimentos em infraestrutura de transporte de cargas, considerando-se seu caráter multidimensional. Para isso, foi proposta metodologia integrando os conceitos de análise de decisão multicritério e de programação matemática, representados pela teoria de utilidade multiatributo (Multi-Attribute Utility Theory - MAUT) e por problema de otimização de fluxos em rede (Minimum Cost Network Flow Problem - MCNFP), respectivamente. No desenvolvimento do modelo foram contemplados critérios de avaliação referentes às dimensões de análise financeira, operacional e ambiental. Posteriormente, foi considerada a aplicação de versões do modelo proposto com diferentes números de períodos de análise em caso ilustrativo, representativo da rede de transporte disponível e planejada da região Norte do Brasil. A aplicação das diversas versões do modelo proposto, de forma geral, apresentou resultados compatíveis com as teorias relacionadas à avaliação deste problema de decisão, incluindo indução à multimodalidade. Algumas versões do modelo apresentaram violações em algumas de suas restrições. Estes resultados adversos não foram plenamente eliminados, devido a limitações das ferramentas adotadas para aplicação. No entanto, foi possível a correção manual destas violações, resultando em soluções viáveis que, apesar de não serem consideradas ótimas, são mais completas do que soluções obtidas por meio de metodologias unidimensionais de análise. Por fim, foram apresentadas recomendações para condução de trabalhos futuros visando eliminação dos resultados adversos do modelo proposto e complementação de sua análise. / The role of transport infrastructure in productivity increases leading to regional social-economic development is widely recognized. Brazil, however, has serious deficiencies in its transport infrastructure, rooted in the country\'s historical development and in the recent decades\' reduction of public investment in the sector. These deficiencies can be observed in Brazil\'s strong focus on roads for cargo transportation, which besides being less efficient than rail and waterways, results in reduced competitiveness of national enterprises. In this context, the aim of this work was to propose a model for evaluating and selecting investments in freight\'s transportation infrastructure, considering its multidimensional character. It was proposed a methodology integrating the concepts of multi-criteria decision analysis and mathematical programming, represented by the Multi-Attribute Utility Theory (MAUT) along with the Minimum Cost Network Flow Problem (MCNFP). The developed model included financial, operational and environmental analysis evaluation criteria. Subsequently, this study applied the proposed model into a case study of the transportation network, available and planned, of the Northern region of Brazil. Overall, the application of various versions of the proposed model yielded results consistent with related evaluation and decision making theories, including induction of multimodality. Some versions of the model presented some violations of its restrictions. These adverse results were not fully eliminated due to the limitations of the application tools utilized. It was possible, however, to manually correct these violations and obtain viable solutions that, while cannot be considered optimal, are more complete than those obtained by single dimension analysis. Finally, recommendations were made for future studies aiming at eliminating the proposed model\'s adverse outcomes, and complementing its analysis.

We address two computational challenges for numerical simulations of Darcy flow problems: rough and uncertain data. The rapidly varying and possibly high contrast permeability coefficient for the pressure equation in Darcy flow problems generally leads to irregular solutions, which in turn make standard solution techniques perform poorly. We study methods for numerical homogenization based on localized computations. Regarding the challenge of uncertain data, we consider the problem of forward propagation of uncertainty through a numerical model. More specifically, we consider methods for estimating the failure probability, or a point estimate of the cumulative distribution function (cdf) of a scalar output from the model. The issue of rough coefficients is discussed in Papers I–III by analyzing three aspects of the localized orthogonal decomposition (LOD) method. In Paper I, we define an interpolation operator that makes the localization error independent of the contrast of the coefficient. The conditions for its applicability are studied. In Paper II, we consider time-dependent coefficients and derive computable error indicators that are used to adaptively update the multiscale space. In Paper III, we derive a priori error bounds for the LOD method based on the Raviart–Thomas finite element. The topic of uncertain data is discussed in Papers IV–VI. The main contribution is the selective refinement algorithm, proposed in Paper IV for estimating quantiles, and further developed in Paper V for point evaluation of the cdf. Selective refinement makes use of a hierarchy of numerical approximations of the model and exploits computable error bounds for the random model output to reduce the cost complexity. It is applied in combination with Monte Carlo and multilevel Monte Carlo methods to reduce the overall cost. In Paper VI we quantify the gains from applying selective refinement to a two-phase Darcy flow problem.

No description available.