As the efficiency potential for the industrial P-type Al-BSF silicon solar cell reaches its limit, new solar cell technologies are required to continue the pursuit of higher efficiency solar power at lower cost. It has been demonstrated in literature that among possible alternative solar cell structures, cells featuring a local BSF (LBSF) have demonstrated some of the highest efficiencies seen to date. Implementation of this technology in industry, however, has been limited due to the cost involved in implementing the photolithography procedures required. Recent advances in solar cell doping techniques, however, have identified ion implantation as a possible means of performing the patterned doping required without the need for photolithography. In addition, past studies have examined the potential for building solar cells on N-type silicon substrates, as opposed to P-type. Among other advantages, it is possible to create N-type solar cells which do not suffer from the efficiency degradation under light exposure that boron-doped P-type solar cells are subject to. Industry has not been able to capitalize on this potential for improved solar cell efficiency, in part because the fabrication of an N-type solar cell requires additional masking and doping steps compared to the P-type solar cell process. Again, however, recent advances in ion implantation for solar cells have demonstrated the possibility for bypassing these process limitations, fabricating high efficiency N-type cells without any masking steps. It is clear that there is potential for ion implantation to revolutionize solar cell manufacturing, but it is uncertain what absolute efficiency gains may be achieved by moving to such a process. In addition to development of a solar specific ion implant process, a number of new thermal processes must be developed as well. With so many parameters to optimize, it is highly beneficial to have an advanced simulation model which can describe the ion implant, thermal processes, and cell performance accurately. Toward this goal, the current study develops a process and device simulation model in the Sentaurus TCAD framework, and calibrates this model to experimentally measured cells. The study focuses on three main tasks in this regard: Task I - Implant and Anneal Model Development and Validation This study examines the literature in solar and microelectronics research to identify features of ion implant and anneal processes which are pertinent to solar cell processing. It is found that the Monte Carlo ion implant models used in IC fabrication optimization are applicable to solar cell manufacture, with adjustments made to accommodate for the fact that solar cell wafers are often pyramidally textured instead of polished. For modeling the thermal anneal processes required after ion implant, it is found that the boron and phosphorus cases need to be treated separately, with their own diffusion models. In particular, boron anneal simulation requires accurate treatment of boron-interstitial clusters (BICs), transient enhanced diffusion, and dose loss. Phosphorus anneal simulation requires treatment of vacancy and interstitial mediated diffusion, as well as dose loss and segregation. The required models are implemented in the Sentaurus AdvancedModels package, which is used in this study. The simulation is compared to both results presented in literature and physical measurements obtained on wafers implanted at the UCEP. It is found that good experimental agreement may be obtained for sheet resistance simulations of implanted wafers, as well as simulations of boron doping profile shape. The doping profiles of phosphorus as measured by the ECV method, however, contain inconsistencies with measured sheet resistance values which are not explained by the model. Task II - Device Simulation Development and Calibration This study also develops a 3D model for simulation of an N-type LBSF solar cell structure. The 3D structure is parametrized in terms of LBSF dot width and pitch, and an algorithm is used to generate an LBSF structure mesh with this parametrization. Doping profiles generated by simulations in Task I are integrated into the solar cell structure. Boundary conditions and free electrical parameters are calibrated using data from similar solar cells fabricated at the UCEP, as well as data from lifetime test wafers. This simulation uses electrical models recommended in literature for solar cell simulation. It is demonstrated that the 3D solar cell model developed for this study accurately reproduces the performance of an implanted N-type full BSF solar cell, and all parameters fall within ranges expected from theoretical calculations. The model is then used to explore the parameter space for implanted N-type local BSF solar cells, and to determine conditions for optimal solar cell performance. It is found that adding an LBSF to the otherwise unchanged baseline N-type cell structure can produce almost 1% absolute efficiency gain. An optimum LBSF dot pitch of 450um at a dot size of 100um was identified through simulation. The model also reveals that an LBSF structure can reduce the fill factor of the solar cell, but this effect can be offset by a gain in Voc. Further efficiency improvements may be realized by implementing a doping-dependent SRV model and by optimizing the implant dose and thermal anneal. Task III - Development of a Procedure for Ion Implanted N-type LBSF Cell Fabrication Finally, this study explores a method for fabrication of ion-implanted N-type LBSF solar cells which makes use of photolithographically defined nitride masks to perform local phosphorus implantation. The process utilizes implant, anneal, and metallization steps previously developed at the UCEP, as well as new implant masking steps developed in the course of this study. Although an LBSF solar cell has not been completely fabricated, the remaining steps of the process are successfully tested on implanted N-type full BSF solar cells, with efficiencies reaching 20.0%.

With the growing interest in converting a wide variety of biomass-based feedstocks to biofuels, there is a need to develop effective procedures for the design and optimization of multi-feedstock biorefineries. The unifying goal of this work is the development of systematic methodologies and procedures for designing flexible multifeedstock biorefineries. This work addresses four problems that constitute building blocks towards achieving the unifying goal of the dissertation. The first problem addresses the design and techno-economic analysis of an integrated system for the production of biodiesel from algal oil. With the sequestration of carbon dioxide from power plant flue gases, algae growth and processing has the potential to reduce greenhouse gas emissions. Algae are a non-food oil feedstock source and various pathways and technologies for obtaining algal oil were investigated. Detailed economic and sensitivity analysis reveal specific scenarios that lead to profitability of algal oil as an alternative feedstock. In the second problem, a new safety metric is introduced and utilized in process design and selection. A case study was solved to assess the potential of producing biodiesel from sewage sludge. The entire process was evaluated based on multiple criteria including cost, technology and safety. The third problem is concerned with incorporating flexibility in the design phase of the development of multi-feedstock biofuel production processes. A mathematical formulation is developed for determining the optimal flexible design for a biorefinery that is to accommodate the use of multiple feedstocks. Various objective functions may be utilized for the flexible plant depending on the purpose of the flexibility analysis and a case study is presented to demonstrate one such objective function. Finally, the development of a systematic procedure for incorporating flexibility and heat integration in the design phase of a flexible feedstock production process is introduced for the fourth problem. A mathematical formulation is developed for use in determining the heat exchange network design. By incorporating the feedstock scenarios under investigation, a mixed integer linear program is generated and a flexible heat exchange network scheme can be developed. The solution provides for a network that can accommodate the heating and cooling demands of the various scenarios while meeting minimum utility targets.

<p>Die Brennstoffzelle ist ein elektrochemischer Reaktor und wandelt chemisch gebundene Energie direkt in elektrische Energie um. In der stationären Energieerzeugung ist der Brennstoffzellenstapel selbst nur ein kleiner Bestandteil des vollständigen Systems. Die Integration aller zusätzlichen Bestandteile, der Peripheriegeräte (Balance-of-Plant) (BoP), ist eine der Hauptaufgaben in der Studie der Brennstoffzellenkraftwerke.</p><p>Diese Untersuchung betrifft die Systemstudie des auf der Schmelz-Karbonat-Brennstoffzelle (MCFC) basierten Kraftwerks. Die Systemstudie ist mit dem Simulationprogramm Aspen PlusTM durchgeführt worden.</p><p>Artikel I beschreibt die Implementierung eines in Aspen PlusTM entwickelten MCFC Stapelmodells, um ein MCFC Kraftwerk zu studieren, das Erdgas als Brennstoff verwendet.</p><p>Artikel II beschreibt, wie unterschiedliche Prozeßparameter, wie Brenngasnutzung und dieWahl des Brennstoffes, die Leistung eines MCFC Kraftwerks </p> / <p>A fuel cell is an electrochemical reactor, directly converting chemically bound energy to electrical energy. In stationary power production the fuel cell stack itself is only a small component of the whole system. The integration of all the auxiliary components, the Balance-of-Plant (BoP), is one of the main issues in the study of fuel cell power plants.</p><p>This thesis concerns the systems studies of molten carbonate fuel cell (MCFC) based power plants. The system studies has been performed with the simulation software Aspen PlusTM.</p><p>Paper I describes on the implementation of a developed MCFC stack model into Aspen PlusTM in order to study an MCFC power plant fueled with natural gas.</p><p>Paper II describes how different process parameters, such as fuel cell fuel utilization, influence the performance of an MCFC power plant.</p> / <p>Bränslecellen är en elektrokemisk reaktor som kan direkt omvandla kemiskt bunden energi till elektrisk energi. I stationär kraftproduktion är själva bränslecellsstapeln endast en mindre komponent i systemet. Integrationen av kringutrustningen, den s.k. Balance-of-Plant (BoP), som tex. pumpar, kompressorer och värmeväxlare är en av huvudfrågeställningarna i studierna av bränslecellskraftverk. Denna avhandling avser systemstudier av mältkarbonatbränslecellsbaserade (MCFC) kraftverk. Systemstudierna har utförts med processimuleringprogramet Aspen PlusTM.</p><p>Artikel I beskriver en utvecklad MCFC-cellmodell, som implementeras som "user model" i Aspen Plus, för att studera ett naturgasbaserat bränslecellskraftverk.</p><p>Artikel II beskriver hur olika processparametrar, som tex bränsleutnyttjande och val av bränsle, påverkar ett MCFC-kraftverks prestanda.</p>

Der Einsatz von digitalen Menschmodellen erlaubt neben einer frühzeitigen ergonomischen Analyse die Gestaltung von Arbeitsprozessen und stellt ein hilfreiches Werkzeug in der Produkt- und Prozessgestaltung dar. Im Rahmen dieses Beitrages soll auf ausgewählte Schwerpunkte der Entwicklung des digitalen Menschmodells „The Smart Virtual Worker“ eingegangen werden. Das Forschungsprojekt soll einen Beitrag zur Lösung, der mit dem demografischen Wandel der Gesellschaft einhergehenden Herausforderungen leisten. Die daraus resultierenden Forschungsschwerpunkte liegen insbesondere in der Einbeziehung von Alterungs- und psychischen Faktoren in die Bewegungsgenerierung des Menschmodells und der Modellierung von Umweltbedingungen. In Umsetzung des Projektes wurde ein erstes Arbeitsszenario erarbeitet, auf dessen Basis die vorgenannten Forschungsaufgaben interdisziplinär gelöst werden sollen.

Strategic business and IT alignment assessment is growing in importance. Different assessment methods have been used to try to pursue the complexity of this dynamic and evolutionary alignment. Despite the fact that alignment is a real problem and a challenge of utmost importance, no consensus can be found on what alignment really is, how it should be measured in the organization in practice, or what measures should be taken to maintain and improve it. Consequently, the key question about how to assess and accomplish (define, identify, measure, maintain and improve) the strategic business and IT alignment is still a great unanswered challenge for many enterprises. In this thesis work, three main research questions were formulated: how can the validity and reliability of an alignment assessment method be improved, what are the dominant topics in the area of alignment, and how to facilitate the analysis of the business and IT governance alignment based on business process simulation and balanced scorecard methods. This is a composite thesis work that includes an introduction and six papers (paper A-F). The main contributions and results of this thesis are described in published and included technical papers. In papers A and B an alternative organization-wide approach and metamodel for assessing strategic business and IT alignment are proposed. Two case studies were performed applying the proposed approach. In paper C, a prioritized diagram of the most widely accepted strategic alignment model, with the purpose of categorizing the most important topics in the research area of strategic business and IT alignment is presented. One of the relevant topics that were identified is governance. In papers D, E and F, there are presented a business process simulation approach and a balanced scorecard method in order to facilitate the assessment of the business and IT governance alignment. An illustrative example of the simulation approach is presented in an appendix of this thesis. This research work aims to improve the decision-making process for business and IT managers at different levels in an enterprise by means of increasing the level of understanding and knowledge as well as by enhancing existing models and methods, for evaluating strategic business and IT alignment. / <p>QC 20101110</p>

Coal-fired power plants are the largest anthropogenic point sources of CO2 emissions worldwide. About 40% of the world's electricity comes from coal. Approximately 49% of the US electricity in 2008 and 23% of the total electricity generation of Canada in 2000 came from coal-fired power plant (World Coal Association, and Statistic Canada). It is likely that in the near future there might be some form of CO2 regulation. Therefore, it is highly probable that CO2 capture will need to be implemented at many US and Canadian coal fired power plants at some point. Several technologies are available for CO2 capture from coal-fired power plants. One option is to separate CO2 from the combustion products using conventional approach such as chemical absorption/stripping with amine solvents, which is commercially available. Another potential alternative, membrane gas separation, involves no moving parts, is compact and modular with a small footprint, is gaining more and more attention. Both technologies can be retrofitted to existing power plants, but they demands significant energy requirement to capture, purify and compress the CO2 for transporting to the sequestration sites. This thesis is a techno-economical evaluation of the two approaches mentioned above along with another approach known as hybrid. This evaluation is based on the recent advancement in membrane materials and properties, and the adoption of systemic design procedures and optimization approach with the help of a commercial process simulator. Comparison of the process performance is developed in AspenPlus process simulation environment with a detailed multicomponent gas separation membrane model, and several rigorous rate-based absorption/stripping models. Fifteen various single and multi-stage membrane process configurations with or without recycle streams are examined through simulation and design study for industrial scale post-combustion CO2 capture. It is found that only two process configurations are capable to satisfy the process specifications i.e., 85% CO2 recovery and 98% CO2 purity for EOR. The power and membrane area requirement can be saved by up to 13% and 8% respectively by the optimizing the base design. A post-optimality sensitivity analysis reveals that any changes in any of the factors such as feed flow rate, feed concentration (CO2), permeate vacuum and compression condition have great impact on plant performance especially on power consumption and product recovery. Two different absorption/stripping process configurations (conventional and Fluor concept) with monoethanolamine (30 wt% MEA) solvent were simulated and designed using same design basis as above with tray columns. Both the rate-based and the equilibrium-stage based modeling approaches were adopted. Two kinetic models for modeling reactive absorption/stripping reactions of CO2 with aqueous MEA solution were evaluated. Depending on the options to account for mass transfer, the chemical reactions in the liquid film/phase, film resistance and film non-ideality, eight different absorber/stripper models were categorized and investigated. From a parametric design study, the optimum CO2 lean solvent loading was determined with respect to minimum reboiler energy requirement by varying the lean solvent flow rate in a closed-loop simulation environment for each model. It was realized that the success of modeling CO2 capture with MEA depends upon how the film discretization is carried out. It revealed that most of the CO2 was reacted in the film not in the bulk liquid. This insight could not be recognized with the traditional equilibrium-stage modeling. It was found that the optimum/or minimum lean solvent loading ranges from 0.29 to 0.40 and the reboiler energy ranges from 3.3 to 5.1 (GJ/ton captured CO2) depending on the model considered. Between the two process alternatives, the Fluor concept process performs well in terms of plant operating (i.e., 8.5% less energy) and capital cost (i.e., 50% less number of strippers). The potentiality of hybrid processes which combines membrane permeation and conventional gas absorption/stripping using MEA were also examined for post-combustion CO2 capture in AspenPlus®. It was found that the hybrid process may not be a promising alternative for post-combustion CO2 capture in terms of energy requirement for capture and compression. On the other hand, a stand-alone membrane gas separation process showed the lowest energy demand for CO2 capture and compression, and could save up to 15 to 35% energy compare to the MEA capture process depending on the absorption/stripping model used.

Le développement des bioraffineries repose sur une conception optimisée d’installations industrielles en synergie comportant un grand nombre de flux de matière et d’opérations unitaires. Le recours à des simulateurs de procédés présente un intérêt certain dans la conception, l’analyse et l’optimisation de tels procédés. Souhaitant initier le développement d’un outil de simulation adapté à ce secteur, nous nous sommes appuyés sur l’exemple d’un procédé d’oxydation de biopolymères par extrusion réactive. Les procédés d’extrusion réactive sont caractérisés par un couplage intime entre écoulement, thermique et cinétiques réactionnelles. Les modalités de ce couplage dépendent des réactions visées. Souhaitant proposer un modèle flexible, intégrable dans un simulateur statique de procédés, et permettant d’atteindre un bon compromis entre la prédictivité et la quantité d’essais nécessaires pour ajuster les paramètres du modèle, nous avons opté pour une approche de modélisation mixte reposant à la fois sur une représentation de l’écoulement à l’aide de réacteurs idéaux et sur des lois de la mécanique des fluides. L’écoulement est modélisé par une cascade de réacteurs continus parfaitement agités (RCPA) avec reflux. Chaque RCPA est caractérisé par un taux de remplissage qui dépend des conditions opératoires. Le calcul du taux de remplissage des RCPA, de la pression matière et des débits circulant entre les RCPA en régime permanent est effectué en réalisant un bilan matière sur chaque RCPA. La température matière dans chacun des RCPA est calculée grâce à un bilan thermique. La modification chimique du matériau est décrite à l’aide de trois réactions : l’oxydation dépolymérisante, la formation de groupements fonctionnels (carbonyles et carboxyles) et la dégradation thermomécanique du biopolymère sous l’effet de la chaleur et des contraintes de cisaillement. L’établissement des équations de bilan de population auxquelles on applique la méthode des moments, permet de calculer simultanément les masses molaires moyennes en nombre et en poids du polymère ainsi que la teneur en agent oxydant dans chacun des RCPA. La viscosité est reliée à masse molaire moyenne. Un algorithme de calcul itératif permet de coupler le bilan matière, le bilan thermique et le calcul réactionnel. Les données expérimentales nécessaires à la validation du modèle ont été fournies par la plate-forme expérimentale mise au point au CVG (Centre de Valorisation des Glucides, Amiens) dans le cadre du programme Synthons. Une méthode d’ajustement des paramètres du modèle à partir d’un nombre minimal de données expérimentales a été proposée, permettant d’évaluer le caractère prédictif du modèle. Le modèle d’extrusion réactive ainsi ajusté a permis de reproduire les résultats expérimentaux obtenus pour différents matériaux, débits, vitesses de rotation, et sur deux extrudeuses detaille et de configuration différentes. L’intégration du modèle d’extrusion réactive dans un simulateur de procédés - le logiciel USIM PAC - a permis de simplifier sa mise en œuvre,offre des perspectives en optimisation et dimensionnement d’équipement et rend possible la simulation de l’opération d’extrusion réactive au sein d’une chaîne de transformation complète. / The development of biorefineries requires integrating and optimizing plants and handling a large number of material flows and unit operations. The development of a process simulator dedicated to this field would thus be of great interest. This is what we intended to initiate by relying on the example of the oxidation of biopolymers by reactive extrusion. Reactive extrusion is characterized by a strong coupling between flow, heat transfer and reaction kinetics. This coupling depends on the desired reactions. We here intended to elaborate aflexible model, being easily integrated into a static process simulator, and enabling to reach agood compromise between the predictive character of the model and the amount of experiments required to adjust model parameters. Therefore, we adopted a hybrid modelling approach combining a flow description based on ideal reactors and continuum mechanics laws. Flow is modeled as a cascade of continuous stirred tank reactors (CSTR) with possible backflow. Flow rates between CSTRs are calculated using physical laws taking into account the operating conditions and geometric parameters of the equipment. Each CSTR is characterized by a filling ratio, which depends on the operating conditions. The calculation of steady-state filling ratio, pressure and flow rates between the CSTRs is achieved by performing a material balance in each CSTR. Material temperature in each CSTR is calculated through a thermal balance. The chemical modification of the material is described using three reactions: the oxidative depolymerization, the formation of functional groups(carbonyl and carboxyl) and the thermomechanical degradation of the biopolymer induced by heating and shearing. The number-averaged and weight-averaged molecular weight of the biopolymer and the oxidant content in each CSTR are computed simultaneously by applying the moment operation to population balance equations. Viscosity is linked to the mean molecular weight. An iterative algorithm enables to couple material balance, thermal balance and reaction kinetics. The experimental data required for model validation were provided by the experimental platform developed at the CVG (Centre de Valorisation des Glucides,Amiens, France) in the frame of the Synthons program. A method was proposed in order to adjust model parameters with a minimal number of experimental data, enabling to assess the predictive character of the model. Once the parameters were adjusted, the reactive extrusion model enabled to reproduce the experimental results obtained with different raw materials,flow rates, screw rotation speeds, and using two extruders with different size and screw configuration. The integration of the reactive extrusion model into a process simulator - the USIM PAC software - enabled to simplify its implementation. This constitutes a promising step in a perspective of process optimization and scale-up, and enables to simulate a reactive extrusion operation within a global plant simulator.

In an attempt to improve the quality in finite element analysis of thermoformed components, a method for predicting the thickness distribution is presented. The strain induced anisotropic material behaviour in the amorphous polymers of concern is also taken into account in the method. The method comprises of obtaining raw material data from experiments, followed by a simulation of the vacuum thermoforming process where hyperelastic material behaviour is assumed. The theory of hyperelasticity that was applied was based on the Ogden model and implemented in the FE-software LS-DYNA. Material behaviour from thermoformed prototypes is examined by experiments and implemented together with the mapped results from the thermoforming simulation in a succeeding FE-model. For the latter, the three-parameter Barlat model was suggested, giving the possibility to account for anisotropic material behaviour based on an initial plastic strain.

Este trabalho descreve a aplicação de redes neurais \"feed-forward\" com três camadas em diferentes áreas da Engenharia Química. O objetivo principal do projeto é a modelagem, simulação e posterior otimização do processo de produção de isopreno empregando técnicas de redes neurais em substituição as equações de modelagem fenomenológica. A planta industrial testada é a unidade de produção de isopreno da BRASKEM (antiga COPENE). O sistema consiste essencialmente de um reator de dimerização e uma série de colunas de destilação. Uma vez que redes neurais são capazes de aprender eficientemente o processo a partir de informações extraídas diretamente de dados da planta, para este trabalho o modelo de rede neural gerado foi construído a partir de dados históricos operacionais coletados a cada 15 minutos durante o período de 1 ano. Em uma primeira etapa é realizada a análise dos dados operacionais de modo a detectar e eliminar erros grosseiros e sistemáticos. Em seguida, a modelagem e simulação do processo são realizadas. O modelo de redes neurais gerado é, então, empregado na otimização qualitativa/quantitativa do processo, construindo um \"grid\" de busca detalhado da região de interesse, através um mapeamento completo da função objetivo no espaço das variáveis de decisão. A segunda etapa diz respeito à predição de azeótropos, visando um melhor entendimento do comportamento do sistema da seção de extração de isopreno. Nas duas etapas, a grande vantagem em utilizar modelos de redes neurais, além de ajustar dados, é a capacidade que estes apresentam em representar eficientemente sistemas multivariáveis, complexos e não lineares, aprendendo o sistema, sem o conhecimento das leis físicas e químicas que o regem. Comparações entre a predição dos modelos propostos e os dados experimentais foram executadas e resultados muito bons foram conseguidos do ponto de vista industrial. ) Esta metodologia fornece informações interessantes e de maior compreensão para a análise dos engenheiros de processo do que os procedimentos convencionais correspondentes. Além disso, este trabalho mostra que a metodologia de redes neurais é promissora para varias aplicações indústrias, tais como análise de dados, modelagem, simulação e otimização de processos, bem como predição de propriedades termodinâmicas. / This work describes the application of a three-layer feed-forward neural network (NN) in different areas of chemical engineering. The main objective of this study is to model, simulate and optimize a real industrial plant, using NN by replacing phenomenological models. The industrial process studied is the isoprene production unit from BRASKEM. The chemical process consists basically of a dimerization reactor and a separation column train. Since NNs are able to extract information from plant data in an efficient manner, for this work, the neural network model was built directly from historical plant data, which were collected every 15 minutes during a period of one year. These data were carefully analyzed in order to identify and eliminate gross error data and non-steady state operation data. The modeling using NN was carried out by parts in order to get information on intermediate streams. Then, the global model was built, by interconnecting each individual model, and used to simulate and optimize the process. The optimization procedure carries on a detailed grid search of the region of interest, by a full mapping of the objective function on the space of decision variables. The second stage of this work deals with the azeotropic prediction using also the neural network approach. The objective of this step was to obtain a better understanding of the system behavior in the isoprene extraction section. Since all the cases studied are non-linear, complex andmultivariable systems, NN approach appears as a technique of interest due to its capability of learning the system without knowledge of the physical and chemical laws that govern it. Comparisons between the model\'s prediction and the experimental data were performed and reasonable results were achieved from an industrial point of view. ) Using neural network approach provides more comprehensive information for an engineer\'s analysis than the conventional procedure. This work shows that the use of NN methodology is promising for several industrial applications, such as data analysis, modeling, simulation and optimization process, as well as thermodynamics properties prediction. However, success in obtaining a reliable and robust NN depends strongly on the choice of the variables involved, as well as the quality of available data set and the domain used for training purposes.

Orientadores: Maria Regina Wolf Maciel, Cesar Benedito Batistella, Rubens Maciel Filho / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química / Made available in DSpace on 2018-08-22T13:19:45Z (GMT). No. of bitstreams: 1 QuinteroPerez_HendersonIvan_D.pdf: 4930705 bytes, checksum: 6c2a9837f37fde815f53e580b02df9cc (MD5) Previous issue date: 2009 / Resumo: O desenvolvimento de biolubrificantes vem sendo estimulado na indústria e na pesquisa, visando diminuir os danos ambientais causados por vazamentos inevitáveis em equipamentos ou motores com utilização principalmente na agricultura e sistemas náuticos. Os biolubrificantes, derivados de óleos vegetais são produtos de grande interesse pela sua elevada biodegradabilidade, além de serem provenientes de fontes renováveis e abundantes na natureza. Atualmente, no Brasil, vem sendo utilizado o óleo de mamona como matéria prima base na síntese de biolubrificantes por ser um produto com valor comercial aceitável e ser abundante na região do nordeste do país e por ter viscosidade e lubricidade adequada para seu uso em lubrificantes sintéticos. No entanto, o óleo de mamona apresenta algumas desvantagens de ordem técnica para a produção de ésteres biolubrificantes pela dificuldade na purificação do próprio éster e na separação dos co-produtos, especialmente quando a reação de transesterificação é feita via catálise alcalina. Visando contornar esses problemas, neste trabalho foram desenvolvidas e avaliadas metodologias de purificação via destilação molecular de filme descendente de um éster biolubrificante produzido por transesterificação do óleo de mamona e álcool isoamílico. Por meio da análise estatística da influência das variáveis operacionais do processo de purificação do biolubrificante foi identificado que é possível obter uma corrente de destilado com teor de éster acima de 97% e um rendimento de éster no destilado de 92% pode ser atingido usando-se temperatura do evaporador de 185°C, temperatura do condensador em 60°C e vazão de alimentação de 10,8 mL/min, quando o processo de separação foi precedido de um primeiro estágio de destilação a vácuo para isolar os componentes mais voláteis. O biolubrificante obtido apresentou valores adequados de viscosidade e índice de viscosidade além de valores do ponto de fulgor e ponto de fluidez promissores para usos em formulas lubrificantes ou como fluido hidráulico. Uma modelagem fenomenológica simplificada do processo de destilação molecular foi implementada no modulo Aspen Custom Modeler (ACM) do software Aspen Tech® versão 7.3, e simulações do processo de purificação de biolubrificantes com análises de sensibilidade das variáveis operacionais foram desenvolvidas para avaliar o rendimento do processo e a pureza do biolubrificante / Abstract: The development of biolubrificants has been stimulated in both industrial and academic environments, aiming to reduce the environmental damage caused by inevitable leakage of mineral lubricating oils in equipment or engines, principally used in agriculture and nautical systems. The biolubrificants derived from vegetable oils are products of great interest for their high biodegradability, and because they are from renewable resources and abundant in nature. Currently, in Brazil, castor oil has been used as raw material in biolubrificant synthesis, as it is a product with acceptable commercial value, abundant in the northeastern region of the country and with adequate viscosity and lubricity for use in synthetic lubricants. However, castor oil has some technical drawbacks for biolubrificant production, such as the difficulty in the ester and co-products separation and purification, especially when the transesterification reaction is done by alkaline catalysts. In order to solve these problems, in this work, purification methodologies through falling film molecular distillation of an ester biolubrificant produced by transesterification reaction of castor oil and isoamyl alcohol were developed and evaluated. Through statistical analysis of the biolubrificant purification process, it was observed that is possible to obtain an distillate stream containing ester above 97% m/m and distillate ester yield of 92% can be achieved using evaporator temperature of 185°C, condenser temperature of 60°C and flow rate of 10,8 mL / min, when the separation process was preceded by a first stage of vacuum distillation for isolate of the most volatile compounds. The obtained biolubrificant showed to have suitable values of viscosity and viscosity index and also the values of flash point and pour point were promising for use in formulate lubricants or hydraulic fluid. Simplified phenomenological modeling of molecular distillation process was implemented in the Aspen Custom Modeler (ACM) from Aspen Tech® 7.3 software and simulations of the molecular distillation process with sensitivity analyses of the operating variables were developed to evaluate the process yield and the biolubrificant purity / Doutorado / Desenvolvimento de Processos Químicos / Doutor em Engenharia Química