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Proton exchange membrane fuel cells (PEMFCs) are one of the leading candidates in alternative energy conversion devices for transportation, stationary, and portable power generation applications. PEMFC systems with their own fuel conversion unit typically consist of several subsystems: a fuel processing subsystem, a fuel cell stack subsystem, a work recovery-air supply subsystem, and a power electronics subsystem. Since these subsystems have different physical characteristics, their integration into a single system/subsystem level unit make the problems of dynamic system synthesis/design and operation/control highly complex. Typically, the synthesis/design optimization of energy systems is based on a single full load condition at steady state. However, a more comprehensive synthesis/design and operation/control optimization requires taking into account part as well as full load conditions for satisfying an optimal efficiency/cost/environmental effect objective. Optimal couple of these various aspects of system development requires dynamic system/subsystem/component modeling and a multi-disciplinary approach which results in an integrated set of diverse types of models and highly effective optimization strategies such as decomposition techniques (e.g., Dynamic Iterative Local-Global Optimization: DILGO). In energy system synthesis/design and operation/control problems, system/ component models are typically treated deterministically, even though input values, which include the specific load profile for which the system or subsystem is developed, can have significant uncertainties that inevitably propagate through the system to the outputs. This deficiency can be overcome by treating the inputs and outputs probabilistically. In this work, various uncertainty analysis methodologies are applied; and among these traditional probabilistic approaches (e.g., Monte Carlo simulation) and the response sensitivity analysis (RSA) method are examined to determine their applicability to energy system development. In particular, these methods are used for the probabilistic (non-deterministic) modeling, analysis, and optimization of a residential 5 kWe PEMFC system, and uncertainty effects on the energy system synthesis/design and operation/control optimization have been assessed by taking the uncertainties into account in the objectives and constraints. Optimization results show that there is little effect on the objective (the operating cost and capital cost), while the constraints (e.g., on the CO concentration) can be significantly affected during the synthesis/design and operation/control optimization. / Ph. D.

The work of this thesis is concerned with the aggregation and advancement of modelling practise as used within modern day product development and optimisation environments making use of Model Based Design ('MBD') and similar procedures. A review of model development and use forms the foundation of the work, with the findings being aggregated into two unique approaches for rapid model development and reconfiguration; the Plug-and-Simulate ('PaS') approach and the Paradigm for Large Model Creation ('PLMC'); each shown to posses its own advantages. To support the MBD process a model optimisation algorithm that seeks to eliminate parameters that are of little or no significance to a simulation is developed. Eliminations are made on the basis of an energy analysis which determines the activity of a number of energy elements. Low activity elements are said to be of less significance to the global dynamics of a model and thus become targets for elimination. A model configuration tool is presented that brings together the PLMC and parameter elimination algorithm. The tool is shown to be useful for rapid configuration and reconfiguration of models and is capable of automatically running the optimisation algorithms thus producing a simulation model that is parametrically and computationally optimised. The response of the plug-and-simulate drivetrain submodels, assembled to represent a front wheel drive drivetrain, is examined. The resulting model is subjected to a torque step-input and an empirically obtained torque curve that characterises the input to a drivetrain undergoing steady acceleration. The model displays the expected response in both its full parameter and parameter reduced versions with simulation efficiency gains observed in the parameter reduced version.

Atualmente, pessoas que não são relacionadas com a área de matemática e computação tem uma aversão muito grande à modelagem matemática e simulação de processos físicos, químicos ou biológicos. Isto é muito aparente na área de Saneamento e Ambiental, pois envolve pessoas de várias áreas. Esta aversão é devida a complexidade dos métodos numéricos para sistemas de equações matemáticas e a necessidade do conhecimento de alguma linguagem computacional. Com o intuito de oferecer uma ferramenta que supre essas deficiências, o programa SAAM foi desenvolvido para ambiente Windows, procurando ter uma metodologia simplificada para o usuário. A principal aplicação do programa é a visualização do que ocorre nos processos antes de obter a estabilidade, ou seja, em regime transiente, pois no regime permanente os cálculos são simples. Os modelos matemáticos mais complexos, como sistemas de equações diferenciais, podem ser resolvidos pelos métodos numérico de Runge-Kutta de 3ª ou 4ª ordem, que estão embutidos no programa. Este trabalho também apresenta exemplos de processos de Engenharia Sanitária e Ambiental para mostrar a aplicação do programa SAAM. / Nowadays, people not related to the area of mathematics and computer science have a great aversion to the mathematical modeling and simulation of physical, chemical and biological processes. This is very apparent in area of Sanitation and Environmental, because it involves people from many areas. This aversion is due to the complexity of numerical methods for systems of mathematical equations and to the necessity of knowledge of some computer language. With the purpose of offering a tool that supplies those deficiency, the software SAAM was developed for Windows, seeking to have a simplified methodology for the user. The major appliance of the software is the show that occurs in the processes before of gaining the stability, or else, in the dynamic state, for the steady-state the calculations are simple. The more complex mathematical models, such as systems of differential equations, can be resolved by the numerical methods of Runge-Kutta of 3rd and 4th order, that are embedded in the program. This work also presents examples of process of Sanitary and Environmental Engineering in a order to show the appliance of the software SAAM.

This work presents two innovative ways to evaluate mining projects. The first is the Activity-Based Costing Approach in mining operations with a product mix. After analyzing and collecting data from an aggregate mine located in Brazil, a cost model was built, and from that, a cost management and analysis methodology of a mine is created. This work has the innovation advantages of using ABC as a tool for planning the operation of the mine, identifying the more profitable products. The second is the use of dynamic simulation in the early stage of Front End Loading (FEL) studies of a Mining Project. In the early stages the global availability (Number of hours a plant is available for production) and production (Number of hours a plant is actually operated with material) time of the process plant are normally assumed based on the experience of the study team. Understanding and defining the hours available at the early stages of the project are important for the future stages of the project, as drastic changes in work hours will impact the economics of the project at that stage. An innovative high-level dynamic modeling approach has been developed to assist in a fast evaluation of assumptions made by the study team. This model incorporates systems or equipment commonly used in mining projects from mine to product stockyard discharge after the process plant. This model includes subsystems that will simulate all the handling components, major processing plant systems required for a mining project. The output data provided by this high-level dynamic simulation approach will enhance the confidence level of engineering carried out during the early stage of the project. This work discusses the technical and economic advantages in using this approach and five test cases comparing with the standard techniques used in mining project FEL studies. At the end, it is concluded that the creation of a cost model to be applied in mining operations is a rewarding investment as it shows the profitable and unprofitable products, and that the use of dynamic simulation in the early stages is technically and economically advantageous. / Este trabalho apresenta duas maneiras inovadoras de avaliar projetos de mineração. A primeira é a Abordagem de Custeio Baseado em Atividades em operações de mineração com mix de produtos. Após coletar e analisar dados de uma mineração de agregados localizada no Brasil, um modelo de custo foi desenvolvido, e a partir deste, uma metodologia de análise e gerenciamento dos custos da mineração é criado. Este trabalho tem a vantagem de inovar ao usar a abordagem ABC como uma ferramenta de planejamento da operação de mina, identificando os produtos mais rentáveis. A segunda é o uso de simulação dinâmica nos estágios iniciais de estudos \"Front End Loading\" (FEL) de Projetos de Mineração. Nos estágios iniciais o tempo de disponibilidade global (número de horas que está disponível para operação) e de produção (número de horas que está realmente operando com material) da usina de beneficiamento são normalmente assumidos baseados na experiência da equipe de projeto. É importante definir estes tempos nos estágios iniciais do projeto, visto que mudanças drásticas nas horas trabalhadas impactará sobre a economia do projeto. Uma inovadora abordagem de modelagem dinâmica de alto nível foi desenvolvida para auxiliar numa avaliação rápida das premissas adotadas pela equipe de projeto. Este modelo incorpora sistemas e equipamentos comumente usados em projetos de mineração, da mina até o descarregamento de material nos pátios de estocagem de produtos depois da usina de beneficiamento. Este modelo inclui subsistemas que simulam todos os componentes de manuseio e principais sistemas da usina de beneficiamento requeridos para um projeto de mineração. Os dados de saída fornecidos por esta abordagem aumentarão o nível de confiança da engenharia realizada durante a fase inicial do projeto. Este trabalho discute as vantagens técnicas e econômicas de utilizar esta metodologia e apresenta uma comparação de cinco casos testes com as técnicas tradicionais usadas nos projetos de mineração em estudos FEL. No final, é concluído que a criação de um modelo de custo para ser usado na operação de mineração é um investimento recompensador, pois mostra os produtos rentáveis e não-rentáveis, e que o uso de simulação dinâmica nos estágios iniciais é tecnicamente e economicamente vantajoso.

The daVinci Research Kit (dVRK) is a research platform that consists of the clinical daVinci surgical robot, provided by Intuitive Surgical to Academic Institutions. It provides an open source software and hardware platform for researchers to study and analyze the current architecture and expand the capabilities of the existing technology. The line between general purpose robotics and medical robotics has segregated the two fields. A significant part of the segregation lies at the software end, where new tools and methods developed in general purpose robotics cannot make it to medical robotics in a short amount of time. This research focuses on the integration of a widely used software architecture for general purpose robotics with the dVRK with the hope of utilizing the research and development from one field to the other. As a first step towards this bridging, a motion planning framework and a dynamic simulator has been developed for the dVRK using ROS. The motion planning framework is aimed to assist the surgeon in performing task with additional safety and machine intelligence. A few use cases have been proposed as well. Lastly, a Matlab Interface has been developed that is standalone in terms of usage and provides capabilities to interact with dVRK.

Understanding and simulating the relationship between urban land-use configuration and patterns of human spatial interaction has been the subject of multi-disciplinary research. Conceptually, it is recognized that the location decisions of several urban actors including individuals, households, firms and public sector institutions, collectively determine the spatial distribution of land-use activities; the emergent land-use patterns, in turn, provide the structural conditions within which flows and interactions between locations occur daily and respond to each other over time. Over the past six decades, various theories and concepts from urban economics, social-physics, transportation studies, and the complexity sciences have underpinned empirical research and development of state-of-the-art simulation models to explore the land-use and travel nexus. Using a case study design and selecting the Kumasi Metropolis, a medium-size metropolis of nearly two-million inhabitants in Ghana, West Africa as the case study area, two main objectives, which reflect research trends and gaps in both the empirical literature and simulation model development have been addressed in this thesis. The first objective was to examine empirically, the location choice behaviour of households and individuals with respect to their residential and job locations, and the mobility patterns associated with the observed home-work location combinations within the metropolis. The second objective was to develop an integrated geospatial and agent-based model to simulate how the residential and job location choice behaviour of heterogeneous households and individuals co-emerge with mobility patterns in the metropolis. The empirical studies presented in this thesis contributes to a deeper understanding of how location-defining attributes at multiple spatial-scales interact with socio-demographic attributes of heterogeneous households and individuals to determine their residential location choice, job location choice and mobility characteristics. The development of the Metropolitan Location and Mobility Patterns Simulator (METLOMP-SIM)—an integrated geospatial and agent-based model also demonstrates how the encoded micro-scale behaviour of purposive households and individuals, interacting with each other and their environment dynamically, could reproduce macro-scale urban location patterns, property market price formation and evolution, and patterns and attributes of spatial flows and interactions anchored on the population’s residential-job location combinations.

O propósito desta Tese é realizar o estudo da implementação do controle avançado do tipo controle preditivo baseado em modelo (MPC) e otimização em tempo real (RTO) em uma unidade de processo industrial usando como ferramentas softwares comerciais de simulação e otimização de processos. As soluções propostas podem ser consideradas como estratégias de integração entre RTO e MPC de uma e duas camadas. Na estratégia de duas camadas, a camada superior que considera um modelo rigoroso não linear do processo computa e envia targets otimizantes à camada dinâmica do MPC, que computa as ações de controle necessárias para alcançar esses targets e estabilizar o processo. Na estratégia de uma camada, mais conhecida como MPC econômico, temos a inclusão do gradiente da função econômica na função custo do controlador preditivo. Ambas as estratégias foram estudadas e suas implementações na coluna de destilação de propeno/propano com integração energética da unidade de produção de propeno da refinaria de Capuava da Petrobras foram simuladas. Este estudo foi realizado em varias etapas. Primeiro, uma simulação dinâmica do processo foi realizada usando o simulador dinâmico SimSci Dynsim® para ser usada como uma planta virtual que também foi usada para a identificação dos modelos usados nos controladores preditivos. Segundo, os algoritmos de controle avançado foram desenvolvidos em Matlab® baseados no controlador preditivo de horizonte infinito (IHMPC), no controlador preditivo robusto (RIHMPC) e no MPC econômico. Terceiro, o algoritmo de RTO foi desenvolvido no pacote de otimização em tempo real Simsci ROMeo®, onde o modelo rigoroso não linear do processo foi implantado incluindo as etapas de simulação, reconciliação de dados e otimização. Quarto, modificações e adaptações dos algoritmos e rotinas desenvolvidas foram feitas para permitir a comunicação de dados em tempo real usando o protocolo de transferência de dados OPC entre Matlab®, Simsci Dynsim® e Simsci ROMeo ®. Finalmente, foram desenvolvidos o sequenciamento e automação dos algoritmos tanto para leitura e escritura de dados, assim como, para a rotina do RTO. Para todas as estratégias propostas nesta Tese, foram incluídos exemplos de simulação representativos onde se pode evidenciar a estabilidade e convergência das estratégias propostas, chegando-se à conclusão que as estruturas propostas de RTO/MPC podem ser implementadas no sistema real. / The aim of this Thesis is to study the implementation of advanced control, specifically, Model Predictive Control (MPC) and real time optimization (RTO) in an industrial process system using tools such as commercial software for process simulation and optimization. The proposed solutions can be considered as integration strategies of RTO and MPC with one and two layers. In the two layer approach, the upper layer that considers a rigorous non-linear steady-state model of the process computes optimizing targets that are sent to the dynamic layer that are based on the MPC, which computes the necessary control actions to reach those targets and stabilize the process system. In the one layer strategy, also called as Economic MPC, the gradient of the economic function is included in the cost function of the predictive controller. Both strategies were studied and their implementation in the energy-recovery propylene/propane splitter system of the propylene production unit at the Capuava Refinery of Petrobras was simulated. In order to accomplish this objective, the work was developed in several steps. Firstly, a dynamic simulation of the process was built in the dynamic simulator Simsci Dynsim® so that it could be used as a virtual plant in which the model identification could also be performed. Secondly, the advanced control algorithms were developed in Matlab® based on the Infinite Horizon Model Predictive Control (IHMPC), the robust predictive controller (RIHMPC) and the Economic MPC. Thirdly, the RTO algorithm was developed in the real-time optimization package Simsci ROMeo®, where the non-linear rigorous model of the process was built including the stages of simulation, data reconciliation and optimization. Fourthly, modifications and adaptation of the developed algorithms and routines were included to allow the real-time data communication considering the OPC data transfer protocol between Matlab®, Dynsim® and ROMeo ®. Finally, a sequence of algorithms was developed and automated for data reading and writing, as well as, for the RTO sequence. For all the strategies developed in this Thesis, representative simulation examples were presented in order to show the closed-loop stability and convergence of the proposed approaches, leading to the conclusion that the proposed RTO/MPC structures can be implemented in the real system.

Este trabalho aborda a modelagem matemática do processo de extração de óleos essenciais por arraste a vapor e a otimização deste processo em escala industrial. Utilizouse dados experimentais de óleos essenciais de alecrim e citronela obtidos em uma unidade industrial de extração por arraste a vapor. O modelo é constituído de um sistema de equações diferenciais parciais, que representam o balanço de massa unidimensional nas fases vapor e sólido. Para resolver o modelo desenvolvido, utilizouse o método das linhas com o uso da técnica de diferenças finitas para discretizar a coordenada espacial e suas derivadas, resultando em um sistema de equações diferenciais ordinárias implementado no simulador EMSO. Os parâmetros do modelo foram estimados pelo método dos poliedros flexíveis, utilizando dois conjuntos de dados experimentais e um terceiro para sua validação. O modelo ajustou-se bem aos dados experimentais industriais, resultando, para duas condições ambientais e geográficas das plantas aromáticas de alecrim, em coeficiente global de transferência de massa de 8,64 x 10 -4 s -1 e 9,10 x 10 -4 s -1, e a constante de equilíbrio de 2,72 x 10 -4 m3=kg e 1,07 x 10 -2m3/kg. Enquanto que para a citronela obteve-se coeficiente global de transferência de massa de 8,29 x 10 -4s -1 e 1,23 x 10 -3 s -1, e constante de equilíbrio de 1,25 x 10 -2 m3/kg e 1,52 x 10 -3 m3/kg. Foi proposto também um problema de otimização para determinar o tempo ótimo de extração e o número de bateladas por dia. Os resultados da otimização do processo indicam que se pode reduzir o tempo de extração, permitindo que outras extrações sejam realizadas por dia, maximizando o volume de óleo extraído ao fim do dia. / This work has as objective the development of a mathematical model of essential oils extraction by steam distillation and the optimization of this process on an industrial scale. We used experimental data obtained from rosemary and citronella in an industrial steam distillation unit. The model consists a system of partial differential equations, which represent the one-dimensional mass balance in steam and solid phases. To solve the developed model, we used the method of lines with the finite differences technique to discretize the spatial coordinate and its derivatives, resulting in a system of ordinary differential equations implemented in the EMSO simulator. The model parameters were estimated by the method of flexible polyhedra, using two experimental runs and a third experimental run to test the model. The model fitted to the experimental data industry, resulting, for two environmental and geographical conditions of rosemary, in mass transfer coefficients of 8,64 x 10 -4 s -1 and 9,10 x 10 -4 s -1, and the equilibrium constant of 2,72 x 10 -4 m3/kg and 1,07 x 10 -2m3/kg. For citronella, the obtained mass transfer coefficient of 8,29 x 10 -4 s -1 and 1,23 x 10 -3 s -1 and equilibrium constant of 1,25 x 10 -2 m3/kg and 1,52 x 10 -3 m3/kg. It was also proposed an optimization problem to determine the optimum extraction time and number of batches per day. The optimization results indicate that the process can reduce the extraction time, allowing other extractions are performed each day, maximizing the essential oil volume extracted in the day.