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O processo de pasteurização tem como objetivo garantir a segurança e qualidade nutricional do alimento e aumentar sua vida de prateleira. O conhecimento da distribuição do tempo de residência (DTR) do alimento em cada etapa do processo contínuo é importante para uma avaliação adequada do processo e das alterações que causa no alimento. Este trabalho tem como objetivo estudar a DTR em um processo de pasteurização contínuo assistido por micro-ondas aplicado a alimentos líquidos e propor modelos de escoamento para representá-la. Para isso, foram realizados experimentos de estímulo-resposta com alimentação tipo pulso por técnica condutimétrica utilizando uma solução saturada de NaCl como traçador. Com isso, foram obtidas as curvas de DTR do sistema completo, dos trocadores de calor das seções de pré-aquecimento e resfriamento, de seis tubos de retenção com diferentes diâmetros e comprimentos (volumes entre 40 e 125 mL) e do sistema de aquisição de dados de condutividade elétrica. Os experimentos foram realizados em quatro vazões volumétricas (0,5, 0,7, 0,9 e 1,1 L/min), a temperatura ambiente (19 a 26 °C) e como fluido de trabalho foi utilizada uma corrente de alimentação de água com concentração 0,5 g/L de NaCl para estabilizar a leitura de condutividade elétrica. Foram realizadas três repetições por vazão para o processo completo, trocadores de calor e tubos de retenção, e cinco repetições por vazão para o sistema de aquisição de dados, dada a maior sensibilidade. Observou-se a necessidade de realizar o procedimento de convolução numérica para avaliar a distorção na curva de DTR do processo causada pelo escoamento na célula do sistema de aquisição de dados. Foram testados cinco modelos de escoamento: dispersão axial, compartimentado PFR+CSTR, tanques em série, convecção generalizada e y-laminar. O critério de ajuste dos modelos foi a minimização do erro quadrático entre valores experimentais e calculados da curva E(t). Os modelos de dispersão axial e y-laminar foram o que apresentaram melhor ajuste para os tubos de retenção e o modelo de convecção generalizada apresentou melhor ajuste para os trocadores de calor. O regime de escoamento durante os experimentos variou entre laminar e de transição (valores de Reynolds entre 1259 e 4238). Os resultados para o sistema completo e trocadores de calor foram satisfatórios, para os tubos de retenção foi observada uma grande incerteza nos valores dos parâmetros e foi observada a importância da convolução numérica em sistemas de pequeno volume. / Pasteurization process aims to ensure the safety and nutritional quality of the food and increase its shelf life. The knowledge of residence time distribution (RTD) of the food in each step of continuous processes is important to evaluate the process and changes that it causes in foods. This work aims to study the RTD in a continuous pasteurization process assisted by microwave applied to liquid foods and propose flow models to represent it. For this reason, stimulus-response experiments by pulse injection were conducted by conductimetric technique using a saturated solution of NaCl as a tracer. Thus, it was obtained the RTD of the complete process, heat exchangers of preheating section and cooling section, six retention tubes with different diameters and lengths (volumes between 40 and 125 mL) and of the electrical conductivity data acquisition system. The experiments were carried out at four volumetric flow rates (0.5, 0.7, 0.9 and 1.1 L/min), at room temperature (19 to 26 °C) and water with 0.5 g/L of NaCl was used as the work fluid to stabilize the electrical conductivity reading. Three repetitions per volumetric flow rate were performed for the complete process, heat exchangers and holding tubes, and five repetitions per volumetric flow rate were performed for the data acquisition system, given the higher sensibility. It was observed the need to apply the numerical convolution procedure to evaluate the distortion in the RTD curve of the process caused by the flow through the data acquisition system. Five flow models were tested: axial dispersion, PFR+CSTR association, tanks in series, generalized convection and y-laminar. The adjustment criterion of the parameters was the minimization of the quadratic error between experimental and calculated E(t) values. The axial dispersion and y-laminar models provided the best adjustments for the holding tubes and the generalized convection model provided the best adjustment for the heat exchangers. The flow regime during the experiments varied between laminar and transition (Reynolds values between 1259 and 4238). The results for the complete system and heat exchangers were satisfactory, for the holding tubes was observed a great uncertainty in the parameters values and was observed the importance of numerical convolution in small volume systems.

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Groundwater is one of the main sources for drinking water and agricultural activities. Various activities of both humans and nature may lead to groundwater pollution. Very often, pollution, or contamination, of groundwater goes undetected for long periods of time until it begins to affect human health and/or the environment. Cleanup technologies used to remediate pollution can be costly and remediation processes are often protracted. A more practical and feasible way to manage groundwater contamination is to monitor and predict contamination and act as soon as there is risk to the population and the environment. Predicting groundwater contamination requires advanced numerical models of groundwater flow and solute transport. Such numerical modeling is increasingly becoming a reference criterion for water resources assessment and environmental protection. Subsurface numerical models are, however, subject to many sources of uncertainties from unknown parameters and approximate dynamics. This dissertation considers the sequential data assimilation approach and tackles the groundwater contamination problem at the port of Rotterdam in the Netherlands. Industrial concentration data are used to monitor and predict the fate of organic contaminants using a three dimensional coupled flow and reactive transport model. We propose a number of 5 novel assimilation techniques that address different challenges, including prohibitive computational burden, the nonlinearity and coupling of the subsurface dynamics, and the structural and parametric uncertainties. We also investigate the problem of optimal observational designs to optimize the location and the number of wells. The proposed new methods are based on the ensemble Kalman Filter (EnKF), which provides an efficient numerical solution to the Bayesian filtering problem. The dissertation first investigates in depth the popular joint and dual filtering formulations of the state-parameters estimation problem. New methodologies, algorithmically similar, but more efficient numerically, are then proposed based on a more consistent derivation with the Bayesian filtering approach. To reduce computational cost, I further extend the formulation of the hybrid EnKF-variational approach to the state parameter estimation problem and propose an adaptive scheme for the specification of the weights of the flow-dependent and static background covariance matrices. The new adaptive hybrid scheme is shown to provide much better results than the EnKF while using a fraction of the ensemble size. The new methods are implemented and successfully tested with a realistic coupled subsurface and transport-reaction model of the port of Rotterdam by assimilating industrial data on biodegradable chlorinated hydrocarbons. The observational design problem for placing hydrologic wells is subsequently considered and a new efficient solution is proposed that combines concepts from both information theory and data assimilation

In this work we develop and analyze algorithms motivated by the parameter estimation problem corresponding to a multilayer aquifer/interbed groundwater flow model. The parameter estimation problem is formulated as an optimization problem, then addressed with algorithms based on adjoint equations, quasi-Newton schemes, and multilevel optimization. In addition to the parameter estimation problem, we consider properties of the parameter to solution map. This includes invertibility (known as identifiability) and differentiability properties of the map. For differentiability, we expand existing results on Fréchet sensitivity analysis to convection diffusion equations and groundwater flow equations. This is achieved by proving that the Fréchet  derivative of the solution operator is Hilbert-Schmidt, under smoothness assumptions for the parameter space. In addition, we approximate this operator by time dependent matrices, where their singular values and singular vectors converge to their infinite dimension peers. This decomposition proves to be very useful as it provides vital information as to which perturbations in the distributed parameters lead to the most significant changes in the solutions, as well as applications to uncertainty quantification. Numerical results complement our theoretical findings. / Ph. D.

The dynamic solution of multiphase flow through porous media is of special interest to several fields of science and engineering, such as petroleum, geology and geophysics, bio-medical, civil and environmental, chemical engineering and many other disciplines. A natural application is the modeling of the flow of two immiscible fluids (phases) in a reservoir. Others, that are broadly based and considered in this work include the hydrodynamic dispersion (as in reactive transport) of a solute or tracer chemical through a fluid phase. Reservoir properties like permeability and porosity greatly influence the flow of these phases. Often, these vary across several orders of magnitude and can be discontinuous functions. Furthermore, they are generally not known to a desired level of accuracy or detail and special inverse problems need to be solved in order to obtain their estimates. Based on the physics dominating a given sub-region of the porous medium, numerical solutions to such flow problems may require different discretization schemes or different governing equations in adjacent regions. The need to couple solutions to such schemes gives rise to challenging domain decomposition problems. Finally, on an application level, present day environment concerns have resulted in a widespread increase in CO₂capture and storage experiments across the globe. This presents a huge modeling challenge for the future. This research work is divided into sections that aim to study various inter-connected problems that are of significance in sub-surface porous media applications. The first section studies an application of mortar (as well as nonmortar, i.e., enhanced velocity) mixed finite element methods (MMFEM and EV-MFEM) to problems in porous media flow. The mortar spaces are first used to develop a multiscale approach for parabolic problems in porous media applications. The implementation of the mortar mixed method is presented for two-phase immiscible flow and some a priori error estimates are then derived for the case of slightly compressible single-phase Darcy flow. Following this, the problem of modeling flow coupled to reactive transport is studied. Applications of such problems include modeling bio-remediation of oil spills and other subsurface hazardous wastes, angiogenesis in the transition of tumors from a dormant to a malignant state, contaminant transport in groundwater flow and acid injection around well bores to increase the permeability of the surrounding rock. Several numerical results are presented that demonstrate the efficiency of the method when compared to traditional approaches. The section following this examines (non-mortar) enhanced velocity finite element methods for solving multiphase flow coupled to species transport on non-matching multiblock grids. The results from this section indicate that this is the recommended method of choice for such problems. Next, a mortar finite element method is formulated and implemented that extends the scope of the classical mortar mixed finite element method developed by Arbogast et al [12] for elliptic problems and Girault et al [62] for coupling different numerical discretization schemes. Some significant areas of application include the coupling of pore-scale network models with the classical continuum models for steady single-phase Darcy flow as well as the coupling of different numerical methods such as discontinuous Galerkin and mixed finite element methods in different sub-domains for the case of single phase flow [21, 109]. These hold promise for applications where a high level of detail and accuracy is desired in one part of the domain (often associated with very small length scales as in pore-scale network models) and a much lower level of detail at other parts of the domain (at much larger length scales). Examples include modeling of the flow around well bores or through faulted reservoirs. The next section presents a parallel stochastic approximation method [68, 76] applied to inverse modeling and gives several promising results that address the problem of uncertainty associated with the parameters governing multiphase flow partial differential equations. For example, medium properties such as absolute permeability and porosity greatly influence the flow behavior, but are rarely known to even a reasonable level of accuracy and are very often upscaled to large areas or volumes based on seismic measurements at discrete points. The results in this section show that by using a few measurements of the primary unknowns in multiphase flow such as fluid pressures and concentrations as well as well-log data, one can define an objective function of the medium properties to be determined, which is then minimized to determine the properties using (as in this case) a stochastic analog of Newton’s method. The last section is devoted to a significant and current application area. It presents a parallel and efficient iteratively coupled implicit pressure, explicit concentration formulation (IMPEC) [52–54] for non-isothermal compositional flow problems. The goal is to perform predictive modeling simulations for CO₂sequestration experiments. While the sections presented in this work cover a broad range of topics they are actually tied to each other and serve to achieve the unifying, ultimate goal of developing a complete and robust reservoir simulator. The major results of this work, particularly in the application of MMFEM and EV-MFEM to multiphysics couplings of multiphase flow and transport as well as in the modeling of EOS non-isothermal compositional flow applied to CO₂sequestration, suggest that multiblock/multimodel methods applied in a robust parallel computational framework is invaluable when attempting to solve problems as described in Chapter 7. As an example, one may consider a closed loop control system for managing oil production or CO₂sequestration experiments in huge formations (the “instrumented oil field”). Most of the computationally costly activity occurs around a few wells. Thus one has to be able to seamlessly connect the above components while running many forward simulations on parallel clusters in a multiblock and multimodel setting where most domains employ an isothermal single-phase flow model except a few around well bores that employ, say, a non-isothermal compositional model. Simultaneously, cheap and efficient stochastic methods as in Chapter 8, may be used to generate history matches of well and/or sensor-measured solution data, to arrive at better estimates of the medium properties on the fly. This is obviously beyond the scope of the current work but represents the over-arching goal of this research. / text

The main objective of this dissertation is to present an adaptation of some finite volume methods used in the resolution of problems arising in sedimentation processes of flocculated suspensions (or sedimentation with compression).<br />This adaptation is based on the utilization of multiresolution techniques, originally designed to reduce the computational cost incurred in solving using high resolution schemes in the numerical solution of hyperbolic systems of conservation laws.

>Magister Scientiae - MSc / Deformation of the western part of the Table Mountain Group rocks during the Cape Orogeny created a series of folds and associated fractures. The subsequent continental break-up of Gondwana led to the development of large fault systems. These exert a major influence on deep and shallow groundwater flow. There are 3 main types of structures that are investigated. The geological contacts between hydraulically different lithologies, the primary characteristics of the sediments comprising the main geological units and the secondary structures developed from the tectonic events. These inter-alia include lithological boundaries, bedding and conjugate joints and large faults. Compartmentalisation of the aquifers by lithological and fault boundaries are the main regional level controls on flow in the study area. Joints are important for local control of flow, but cumulatively exert a regional effect as well. These controls exert a strong 3 dimensional impact on flow patterns within the area. Geological cross sections and detailed fieldwork combined with the conceptual models proposed are used to determine groundwater flow and the extent of the flow constraints. There is heterogeneity in the fault characteristics whilst there is consistence in the impermeable aquitards. These effect boundaries at the base of the aquifer, divide the aquifer into upper and lower units and cap the top of the aquifer. Using water level data, EC and pH an attempt is made to establish patterns created by structures, mainly faults. There appears to be some control of these shown by patterns seen on contour plots of the data. Understanding of the structures can significantly alter the way the available data could be interpreted. The integration of all available data into the conceptual model provides an effective research tool, which opens up further avenues for new approaches and methods for continued research in this area.

The primary purpose of this dissertation is to develop the arguments for reporting directly on a company's cash flows in its published financial statements. Specifically, the Free Cash Flow (FCF) model of economist Joel Stern is analyzed and critiqued as a basis for a revised reporting scheme.

The electric power system is among the biggest and most complex man-made physical network worldwide. The increase of electricity demand, the integration of ICT technologies for the modernization of the electric grid and the introduction of intermittent renewable generation has resulted in further increasing the complexity of operating and planning the grid optimally. For this reason the analysis of large-scale power systems considering all state variables is a very complicated procedure. Thus, it is necessary to explore methods that represent the original network with smaller equivalent networks in order to simplify power system studies. The equivalent network should provide an accurate and efficient estimation of the behavior of the original power system network without considering the full analytical modelling of the grid infrastructure.   This thesis investigates partitioning methods and reduction methodologies in order to develop a proper reduction model. The K-means and K-medoids clustering algorithms are employed to partition the network into numerous clusters of buses. In this thesis the Radial, Equivalent, and Independent (REI) method is further developed, implemented, and evaluated for obtaining a reduced, equivalent circuit of each cluster of the original power system. The basic idea of REI method is to aggregate the power injections of the eliminated buses to two fictitious buses through the zero power balance network.   The method is implemented using Julia language and the PowerModels.jl package. The reduction methodology is evaluated using the IEEE 5-bus, 30-bus, and 118-bus systems, by comparing a series of accuracy and performance indices. Factors examined in the comparison include the chosen number of clusters, different assumptions for the slack bus as well as the effect of the imposed voltage limits on the fictitious REI buses. / Elsystemet är ett av de största och mest komplexa människotillverkade fysiskanätverken i världen. Ökad elförbrukning, integration av informationsteknik föratt modernisera elnäten samt införandet av varierande förnybar elproduktion harresulterat i ytterligare ökad komplexitet för att driva nätet optimalt. Därför ärdet mycket komplicerat att analysera storskaliga elsystem samtidigt som man tarhänsyn till alla tillståndsvariabler. Det är således nödvändigt att utforska metoderför att modellera det ursprungliga nätverket med ett mindre ekvivalent nätverk föratt underlätta studier av elsystem. Det ekvivalenta nätverket ska ge en noggrann ocheffektiv uppskattning av det ursprungliga systemets egenskaper utan att inkludera enkompletta analytisk modell av nätverkets stuktur.Den här rapporten undersöker metoder för att dela upp och reducera ett nätverkför att få fram en lämplig ekvivalent modell. Klusteranalysalgotmerna K-meansoch K-medoids används för att dela in nätverket i ett antal kluster av noder. Irapporten vidareutvecklas, implementeras och utvärderas REI-metoden för att ta framreducerade ekvivalenta nätverk för varje kluster i det ursprungliga systemet. Dengrundläggande idén med REI-metoden är att den aggregerar elproduktionen i deelminerade noderna i två fiktiva noder genom ett nolleffektbalansnätverk.Metoden är implementerad i programspråket Julia och programpaketetPowerModels.jl. Reduceringsmetoderna utvärderas på IEEE:s system med 5 noder,30 noder respektive 118 noder, genom att jämföra ett antal index för noggrannhetoch prestanda. De faktorer som undersäks i jämförelsen inkluderar det valda antaletkluster, olika antagande om slacknoden samt följderna av spänningsgränserna för defiktiva REI-noderna.v