No description available.

No description available.

<p> A new computer executive system for the steady state simulation of chemical processes has been developed which combines modular (GEMCS) approach with the simultaneous linear equation (SYMBØL) approach to simulation. In the combined system, a GEMCS simulation, using non-linear models, is used to generate the coefficients for the set of linear equations describing the process. This linear system of equations may also include the constraints on the process which dictate the operating conditions for the actual process. The solution of the linear equations then provide new operating conditions (feed flowrates together with the component flowrates in the recycle streams) for the modular simulation, which in turn provides new coefficients; etc. This iterative procedure is automatically continued until the system is converged to the desired point. </p> <p> A modular simulation for an actual Naphtha Reforming Plant has also been achieved and it was used as a test case to demonstrate the use and effectiveness of this new executive system. In the course of developing this simulation, the application of a method for correcting plant data was demonstrated. This is the first real application of this method to be reported in the current literature. </p> / Thesis / Master of Engineering (ME)

No description available.

Se tiene por entendida a la simulación como una herramienta científica que genera diversos contextos a los cuales se puede ver incluida a la empresa, mejorando los cuellos botella de la empresa, tiempo ciclo o costos elevados, con la finalidad de mejorar por ejemplo la productividad, eficiencia o rentabilidad. En base a ello para el presente trabajo de investigación se toma como objeto de estudio a la línea de producción de pollos frescos y limpios de la empresa avícola “Fénix SAC” la cual opera de manera ineficiente debido a que se registran problemas en los puestos de trabajo tanto físicos, como de ruido, iluminación, termomagnético y disergonómico. Para esto se ha buscado realizar propuestas de mejora que conlleven a incrementar la productividad en la empresa mediante la simulación de procesos. Específicamente hablando, se desarrolló un diagnóstico del proceso productivo, luego se ha elaborado propuestas de mejora sobre los indicadores en base al estudio de puestos de trabajo, luego se simulo la línea de producción antes y después de las mejoras propuestas, y por último se estimó la viabilidad económica de la propuesta. Como resultado se obtuvo que existirá un incremento de la productividad económica del 1%, en la MOD se registró un incremento del 32%, en cuanto a la productividad laboral 29,1%. En cuanto a la viabilidad económica, con respecto al VAN, TIR, B/C y PRI, se obtuvo 119 516.67 soles, 65.28%, 1.75 y 1 año con 3 meses y 17 días, respectivamente hablando. / Simulation is understood as a scientific tool that generates various contexts in which the company can be seen to be included, improving the bottlenecks of the company, cycle time or high costs, in order to improve, for example, productivity, efficiency or profitability. Based on this, for the present research work, the production line of fresh and clean chickens of the poultry company "Fénix SAC" is taken as an object of study, which operates in an inefficient manner due to the fact that problems are registered in the positions of physical, noise, lighting, thermomagnetic and disergonomic work. For this, we have sought to make improvement proposals that lead to increased productivity in the company through process simulation. Specifically speaking, a diagnosis of the production process was developed, then improvement proposals were made on the indicators based on the study of jobs, then the production line was simulated before and after the proposed improvements, and finally it was estimated the economic viability of the proposal. As a result, it was obtained that there will be an increase in economic productivity of 1%, in the MOD an increase of 32% was registered, in terms of labor productivity 29.1%. Regarding the economic viability, with respect to the VAN, IRR, B/C and PRI, 119 516.67 soles were obtained, 65.28%, 1.75 and 1 year with 3 months and 17 days, respectively speaking.

Inom dagens läkemedelsindustri finns en strävan efter ständiga förbättringar och kontinuerligt arbete med hållbarhet. Detta beror på att industrin vill ta hänsyn till miljön och samhället, men även kravställningar och regleringar från intressenter. Att följa kravställningar samt hålla ett gott arbete inom hållbarhet kan bidra till en mer ansvarsfull industri. Ett sätt att göra det är genom optimering av resursanvändningen baserat på identifiering och förbättring av överflödig konsumtion och miljöpåverkan. Denna studie har som syfte att identifiera och analysera möjliga hållbarhetsinriktade problemområden genom processimulering och datavisualisering vid produktion av en aktiv substans (API) för läkemedel. Med hjälp av simuleringsmodeller och datavisualisering/dataanalys kan läkemedelsindustrin bli kostnadseffektiv och uppleva mindre risk vid analysering av förbättringsmöjligheter av processer. Genom simulering och dataanalys kan resursanvändningen optimeras utifrån koldioxidavtrycket och mängden förbrukad resurs för tillverkningen av API. Studien besvarar följande frågeställningar; (1) Vilka problem identifieras genom processimulering och datavisualisering med resursutnyttjande och miljöpåverkan av en produkt inom läkemedelsindustrin? (2) Vilka effekter får förbättringsåtgärderna, baserade på de identifierade problemen, på resursutnyttjandet och miljöpåverkan av en produkt inom läkemedelsindustrin? Genom datainsamlingen och ett samarbete med medarbetarna skapades en simuleringsmodell och en datavisualisering på resursanvändningen för samtliga processer vid tillverkningen av en aktiv substans för läkemedel. Därmed identifierades två problemområden, vilket var följande; (1) Användning av lösningsmedel 6, vilket stod för 53% av det totala koldioxidavtrycket [kg eCO2] vid API produktionen för ett läkemedel. (2) Överflödig vattenkonsumtion vid anläggningen där API produktionen skedde. Genom att förbättra dessa identifierade problemområden kan företaget förbättra sin resursutnyttjande samt minska miljöpåverkan. Det innebär att företaget kan säkerställa ekonomisk, ekologisk och social hållbarhet med sitt hållbarhetsarbete. Rekommendationer för framtida studier inkluderar att implementera de presenterade förbättringsåtgärderna och studera effekten av dessa förbättringar i relation till koldioxidavtryck [kg eCO2] och resursutnyttjande. / Today's pharmaceutical industry works for continuous improvement and continuous work with sustainability. This is because the industry wants to lower the impact on the environment and society, but also requirements and regulations from stakeholders. By following requirements and working with sustainability the industry takes more responsibility. This can be achieved by, for example, optimizing resource utilization to identify and improve excess consumption and environmental impact. The purpose of this study is to identify and analyze possible sustainability-oriented problem areas through process simulation and data visualization in the production of an active pharmaceutical ingredient (API). With the help of simulation models and data visualization/data analysis, the pharmaceutical industry can be cost-effective and experience less risk when analyzing opportunities for improvement in processes. Through simulation and data analysis, the use of resources can be optimized based on the carbon footprint and the amount of resources consumed for the manufacture of API. The study answers the following questions: (1) What problems are identified through process simulation and data visualization with resource utilization and environmental impact of a product in the pharmaceutical industry? (2) What effects do the improvement measures, based on the identified problems, have on the resource utilization and environmental impact of a product in the pharmaceutical industry? Through data collection and collaboration with the employees, a simulation model and a data visualization of the resource use for all processes to manufacture an active substance for pharmaceuticals was created. Thus, two problem areas were identified, which were as follows; (1) Use of solvent 6, which accounted for 53% of the total carbon footprint [kg eCO2] in API production for a drug. (2) Excess water consumption at the facility where the API production took place. By improving these identified problem areas, the company can improve its resource utilization and reduce environmental impact. This means that the company can improve economic, ecological and social sustainability with its sustainability work. Recommendations for future studies include implementing the presented improvement measures and study the effect of these improvements in relation to carbon footprint and resource usage.

There has been renewed significance for innovative energy conversion technologies, particularly the heat recovery-to-power technologies for sustainable power generation from renewable energies and waste heat. This is due to the increasing concern over high demand for electricity, energy shortage, global warming and thermal pollution. Among the innovative heat recovery-to- power technologies, the proposed trilateral flash cycle (TFC) is a promising option, which presents a great potential for development. Unlike the Rankine cycles, the TFC starts the working fluid expansion from the saturated liquid condition rather than the saturated, superheated or supercritical vapour phase, bypassing the isothermal boiling phase. The challenges associated with the need to establish system design basis and facilitate system configuration design-supporting analysis from proof-of-concept towards a market-ready TFC technology are significant. Thus, there is a great need for research to improve the understanding of its operation, behaviour and performance. The objective of this study is to develop and establish simulation tools of the TFCs for improving the understanding of their operation, physics of performance metrics and to evaluate novel system configurations for low-grade heat recovery-to-power generation. This study examined modelling and process simulation of the TFC engines in order to evaluate their performance metrics, predictions for guiding system design and parameters estimations. A detailed thermodynamic analysis, performance optimization and parametric analysis of the cycles were conducted, and their optimized performance metrics compared. These were aimed at evaluating the effects of the key parameters on system performances and to improve the understanding of the performance behaviour. Four distinct system configurations of the TFC, comprising the simple TFC, TFC with IHE, reheat TFC and TFC with feed fluid-heating (or regenerative TFC) were examined. Steady-state steady-flow models of the TFC power plants, corresponding to their thermodynamic processes were thermodynamically modelled and implemented using engineering equation solver (ESS). These models were used to determine the optimum synthesis/ design parameters of the cycles and to evaluate their performance metrics, at the subcritical operating conditions and design criteria. Thus, they can be valuable tools in the preliminary prototype system design of the power plants. The results depict that the thermal efficiencies of the simple TFC, TFC with IHE, reheat TFC and regenerative TFC employing n-pentane are 11.85 - 21.97%, 12.32 - 23.91%, 11.86 - 22.07% and 12.01 - 22.9% respectively over the cycle high temperature limit of 393 - 473 K. These suggest that the integration of an IHE, fluid-feed heating and reheating in optimized design of the TFC engine enhanced the heat exchange efficiencies and system performances. The effects of varying the expander inlet pressure at the cycle high temperature and expander isentropic efficiency on performance metrics of the cycles were significant. They have assisted in selecting the optimum-operating limits for the maximum performance metrics. The thermal efficiencies of all the cycles increased as the inlet pressures increased from 2 - 3 MPa and increased as the expander isentropic efficiencies increased from 50 - 100%, while their exergy efficiencies increased. This is due to increased net work outputs that suggest optimal value of pressure ratios between the expander inlets and their outlets. A comprehensive evaluation depicted that the TFC with IHE attained the best performance metrics among the cycles. This is followed by the regenerative TFC whereas the simple TFC and reheat TFC have the lowest at the same subcritical operating conditions. The results presented show that the performance metrics of the cycles depend on the system configuration, and the operating conditions of the cycles, heat source and heat sink. The results also illustrate how system configuration design and sizing might be altered for improved performance and experimental measurements for preliminary prototype development.

There has been renewed significance for innovative energy conversion technologies, particularly the heat recovery-to-power technologies for sustainable power generation from renewable energies and waste heat. This is due to the increasing concern over high demand for electricity, energy shortage, global warming and thermal pollution. Among the innovative heat recovery-to- power technologies, the proposed trilateral flash cycle (TFC) is a promising option, which presents a great potential for development. Unlike the Rankine cycles, the TFC starts the working fluid expansion from the saturated liquid condition rather than the saturated, superheated or supercritical vapour phase, bypassing the isothermal boiling phase. The challenges associated with the need to establish system design basis and facilitate system configuration design-supporting analysis from proof-of-concept towards a market-ready TFC technology are significant. Thus, there is a great need for research to improve the understanding of its operation, behaviour and performance. The objective of this study is to develop and establish simulation tools of the TFCs for improving the understanding of their operation, physics of performance metrics and to evaluate novel system configurations for low-grade heat recovery-to-power generation. This study examined modelling and process simulation of the TFC engines in order to evaluate their performance metrics, predictions for guiding system design and parameters estimations. A detailed thermodynamic analysis, performance optimization and parametric analysis of the cycles were conducted, and their optimized performance metrics compared. These were aimed at evaluating the effects of the key parameters on system performances and to improve the understanding of the performance behaviour. Four distinct system configurations of the TFC, comprising the simple TFC, TFC with IHE, reheat TFC and TFC with feed fluid-heating (or regenerative TFC) were examined. Steady-state steady-flow models of the TFC power plants, corresponding to their thermodynamic processes were thermodynamically modelled and implemented using engineering equation solver (ESS). These models were used to determine the optimum synthesis/ design parameters of the cycles and to evaluate their performance metrics, at the subcritical operating conditions and design criteria. Thus, they can be valuable tools in the preliminary prototype system design of the power plants. The results depict that the thermal efficiencies of the simple TFC, TFC with IHE, reheat TFC and regenerative TFC employing n-pentane are 11.85 - 21.97%, 12.32 - 23.91%, 11.86 - 22.07% and 12.01 - 22.9% respectively over the cycle high temperature limit of 393 - 473 K. These suggest that the integration of an IHE, fluid-feed heating and reheating in optimized design of the TFC engine enhanced the heat exchange efficiencies and system performances. The effects of varying the expander inlet pressure at the cycle high temperature and expander isentropic efficiency on performance metrics of the cycles were significant. They have assisted in selecting the optimum-operating limits for the maximum performance metrics. The thermal efficiencies of all the cycles increased as the inlet pressures increased from 2 - 3 MPa and increased as the expander isentropic efficiencies increased from 50 - 100%, while their exergy efficiencies increased. This is due to increased net work outputs that suggest optimal value of pressure ratios between the expander inlets and their outlets. A comprehensive evaluation depicted that the TFC with IHE attained the best performance metrics among the cycles. This is followed by the regenerative TFC whereas the simple TFC and reheat TFC have the lowest at the same subcritical operating conditions. The results presented show that the performance metrics of the cycles depend on the system configuration, and the operating conditions of the cycles, heat source and heat sink. The results also illustrate how system configuration design and sizing might be altered for improved performance and experimental measurements for preliminary prototype development.

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.

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.