Integrated Chemical Processes in Liquid Multiphase Systems

The essential principles of green chemistry are the use of renewable raw materials, highly efficient catalysts and green solvents linked with energy efficiency and process optimization in real-time. Experts from different fields show, how to examine all levels from the molecular elementary steps up to the design and operation of an entire plant for developing novel and efficient production processes

Use of mathematical methods in the resolution of chemical engineering problems

This thesis consists of a compendium of five works that illustrate the utilization of selected mathematical methods to solve specific chemical engineering problems. Hence, the thesis is intended to cover both, a review of fundamental mathematical procedures for the solution of models raised from chemical phenomena, and a demonstration of their effectiveness to obtain useful novel significant results. The opening paper explores diverse global optimization algorithms to adjust both kinetic constants and the binary interaction parameters (BIPs) for the Peng-Robinson equation of state to the experimental data. Those parameters are essential to determine the model raised from the supercritical transesterification of triolein with methanol to produce biodiesel, with CO2 as cosolvent, consisting of three reversible reaction in series. Here, a novel model merging the ordinary differential equations system raised from kinetic mechanism and the time-dependent thermodynamic state of the complex mixture is presented for diverse operating conditions. Among all results obtained, novel binary interaction coefficients for the intermediate reaction species (dioleins and monooleins) highlight. The second and fourth papers included in this thesis are aimed at the study of lanolin extraction from raw wool, using 5% ethanol in CO2. The former explores solid lanolin extraction under near-critical conditions by means of a mass-transfer model based on the shrinking-core concept, while the latter is addressed at the liquid lanolin supercritical extraction. Both models result in a partial differential equations (PDEs) system determined by the solubility of multiphasic lanolin, Henry-type partition coefficient and the lanolin mass transfer coefficient. Hence, in each paper the raised PDEs system is solved through a different method: in the second paper orthogonal collocation method is employed, while in the fourth paper finite differences method is used combined with the numerical integration of an expression previously obtained by means of the Laplace transform. Finally, an optimization procedure is used in order to fit the extraction parameters to the experimental data, achieving coherent results that agree well with those previously reported. Between the cases exposed, liquid lanolin extraction is significantly complex to model because of the diffusion phenomena that may occur inside the two lanolin fraction mixture added to the diffusion of solvent in the interphase. Therefore, in the third work a nonlinear autoregressive exogenous neural network model is designed to predict the outcoming extracted fraction of lanolin at diverse temperatures, pressures, solvent mass flow rates, wool packing densities and times. The problem with the scarce data available for training of the neural network is overcome by augmenting experimental data using an empirical Weibull function, which correctly predicts the lanolin breakthrough at the extractor exit. This hybrid Weibull - Neural Network algorithm results in a low prediction error and conform a powerful tool for optimizing operating conditions, proved by the fast convergence of genetic algorithm procedure. This thesis closes with Molecular Dynamics simulations for peptide-folding studies, followed by a Principal Component Analysis (PCA) and clustering analysis to understand the Free Energy Landscape of the peptide (FEL). Those methods are aimed at assessing the conformational profile of bombesin, a peptide with interest in drug design as a possible novel agonist and/or antagonist in the fight against cancer. Results suggest that the peptide adopts mainly helical structures at the C-terminus and, to a lesser extent, hairpin turn structures at the N-terminus. Those results agree with those available from NMR in a 2,2,2-trifluoroethanol/water (30% v/v), and point out a suitable a-helix conformation for binding where Trp8 and His12 interaction has a significant role.Aquesta tesi consta d'un compendi de cinc treballs que il·lustren la utilització de mètodes matemàtics per resoldre problemes específics d'enginyeria química. Per tant, la tesi està destinada a ser una revisió dels procediments matemàtics fonamentals per a la solució de models derivats de fenòmens químics i, a més, una demostració de la seva efectivitat per obtenir resultats útils i innovadors. L'article que obre la tesi explora diferents algoritmes d'optimització global per ajustar tant les constants cinètiques com el Paràmetres d'Interacció Binària (PIB) per a l'equació d'estat de Peng Robinsos a les dades experimentals. Aquests paràmetres són essencials per determinar el model derivat de la transesterificació supercrítica de la trioleïna amb metanol per produir biodièsel, amb CO2 com a cosolvent, que consisteix en tres reaccions reversibles en sèrie. Aquí, es presenta un nou model que fusiona el sistema d'EDOs derivat del mecanisme cinètic i l'estat termodinàmic de la barreja per a condicions de funcionament diverses. Entre tots els resultats obtinguts, destaquen els nous PIBs trobats per a les espècies de reacció intermèdies. El segon i quart treball inclosos en aquesta tesi estan destinats a l'estudi de l'extracció de lanolina de llana crua amb 5% d'etanol en CO2. El primer explora l'extracció de lanolina sòlida en condicions gairebé crítiques mitjançant un model de transferència de massa basat en el concepte del nucli minvant, mentre que el segon s'adreça al cas de l'extracció supercrítica de lanolina líquida. Ambdós models donen com a resultat un sistema d'EDPs determinat per la solubilitat de la lanolina multifàsica, el coeficient de partició de Henry i el coeficient de transferències de massa. Per tant, a cada article el sistema d'EDPs obtingut es resol mitjançant un mètode diferent: en el article s'utilitza un mètode de col·laboració ortogonal, mentre que en el quart s'utilitza el mètode de diferències finites combinat amb la integració numèrica d'una expressió obtinguda mitjançant la Transformada de Laplace. Finalment, es porta a terme una optimització per ajustar els paràmetres d'extracció a les dades experimentals, aconseguint resultats coherents que coincideixen amb els reportats anteriorment. Entre els casos expotsats, l'extracció de lanolina líquida és significativament complexa de modelar a causa dels fenòmens de difusió que es poden produir a l'interior de les dues fraccions de lanolina a més de la difusió del dissolvent en la interfase. Per tant, en el tercer treball es dissenya un model de xarxa neuronal exògena no lineal autoregressiva per predir la fracció extreta de lanlina a diverses temperatures, pressions, cabals de dissolvent, densitats d'empaquetament i temps. El problema derivat de l'escassetat de dades disponibles per a l'entrenament de la xarxa neuronal es supera amb l'augment d'aquestes mitjançant una funció de Weibull empírica, que prediu correctament l'avanç de la lanolina a la sortida de l'extractor. Aquest algoritme híbrid Weibull - xarxa neuronal resulta en un baix error de predicció i conforma una potent eina per optimitzar les condicions operatives, demostrada per la ràpida convergència de l'algoritme genètic utilitzat. Aquesta tesi tanca amb simulacions de Dinàmica Molecular per a l'estudi del plegament de pèptids seguint d'un Anàlisi de Components Principals (ACP) i del "clustering" per a l'anàlisi del Paisatge d'Energia Lliure (PEL). L'objectiu és avaluar el perfil conformacional de la bombesina, un pèptid amb interès en el disseny de fàrmacs com a possible nou agonista i/o antagonista en la lluita contra el càncer. Els resultats suggereixen que el pèptid adopta estructures helicoïdals principalment al extrem C, i també en menor mesura estructures de forquilla al extrem N. Aquests resultats coincideixen amb els disponibles de RMN en 2,2-trifluoroetanol/aigua (30% v/v) i indiquen una conformació d’hèlix a adequada per a la unió on la interacció Trp8 i His12 té un paper important

Application of chemical kinetic modeling to improve design and performance criteria for a practical incineration system

In this study, detailed thermo-chemical kinetics with networked ideal reactor model were applied to simulate a practical combustion system -the Secondary Combustion Chamber (SCC) of the Rotary Kiln incineration Simulator (RKIS) at the EPA facility at Research Triangle Park, NC. The networked ideal model was developed using analysis of reactor geometry, temperature profile measurements, and SO2 tracer data provided by EPA. A computer simulation of the networked model was developed using the CHEMKIN H library. A parallel effort considered the effects of non-ideal mixing on detailed thermo-kinetic, simulations. Specifically, an alternate approach was developed to solve the Partially Stirred Reactor (PaSR) model that allowed the incorporation of large detailed mechanisms. Both ideal and non-ideal modeling approaches were compared with experimental data gathered on a Toroidal Jet Stirred Combustor (TJSQ and the SCC at EPA. SCC experiments measured Product of Incomplete Combustion (PIC) formation of surrogate chlorinated wastes (CCl4 and CH2Cl2)lwhile the TSJC experiments measured PIC formation in ethylene/air combustion for fuel-lean conditions near blowout and fuel-rich conditions. Analysis of the geometry and temperature profiles of the SCC suggested the existence of up to four distinct mixing zones. The RTDs, which were resolved from the tracer studies, further supported a multiple PSR model. A model was chosen based on the best fit to SO2, tracer data and consistency with physical geometry, resulting flow patterns, and temperature measurements. A thermo-kinetic mechanism developed by Chiang (1995) was applied to the model. The model results did not agree well with the experimental data. However, it followed many of the underlying trends revealed by the data. Sensitivity analysis of the parameters was used to further explore trends and recommend potential design improvements to reduce PIC formation. An alternate solution technique was developed for the PaSR which approximated mean conditions and solved the deterministic model to refme the approximation and eventually converge on a solution. The approximation, direct integration, and convergence technique compared favorably with the published Monte Carlo modeling calculations, but used, on average, less than 1/200th of the CPU time. This new technique allowed use of considerably larger detailed mechanisms. Additionally, a generalized PaSR model was proposed to account for the effects of non-ideal macromixing

Controlo de temperatura de um gasificador de biomassa

In recent history, the growing environmental crisis and the unsustainable overuse of fossil fuels have become a catalyst for the development of environmentally friendly or carbon neutron energy sources. Such fact lead to the reemergence of gasification in the research and development community. This technology was prominent during World War II due to the unavailability of oil existent at that time, mostly using coal as fuel. With the end of the war, so came the end of its development. Initially, the literature will be reviewed in order to assess the instrumentation technologies needed to measure the gasification process’ operational parameters, and thus, allow its monitoring and control. In order to facilitate the analysis of the data from the developed instrumentation system, a visualization tool was developed. The literature was then reviewed again in order to find the most suitable model topology for the gasification process. This revealed neural networks as the most reliable model architecture for such endeavor. A gasification model was then devised using experimental data present in the literature. The devised model was then used to establish a simulation and controller design environment. This enabled the development of Model Predictive Controller to control the temperature inside the gasifier. The devised model showed great potential as a prediction model, in spite of the deterioration presented when used as a simulator. The developed controller was able to stabilize the model generated output for all tested set-points. The develop work constitutes a solid ground for future work.O desenfreado crescimento da crise ambiental e uso insustentável de combustíveis fósseis vivido nas últimas décadas tem vindo a tornar-se num catalisador na busca de soluções carbonicamente neutras de produção de energia. Este facto levou ao ressurgimento dos processos de gasificação, principalmente de biomassa, como um tema na comunidade de pesquisa e desenvolvimento. Esta tecnologia foi predominante durante a segunda guerra mundial, período no qual a dificuldade de obtenção de petróleo levou acréscimo da sua necessidade, sendo carvão o combustível utilizado. Com o fim da guerra, veio também o fim do seu desenvolvimento. Inicialmente, será realizada uma revisão de literatura que culminará na escolha dos instrumentos de medição e atuação necessários para proceder à monitorização e controlo dos parâmetros operacionais do processo de gasificação. De modo a facilitar a analise dos dados presentes nestes sensores foi desenvolvida uma aplicação de visualização de informação. Findada esta etapa procedeu-se a uma nova revisão da literatura focada na procura de um modelo para o processo de gasificação. Esta revisão revelou as redes neuronais como sendo a melhor topologia para descrever o processo. Utilizando dados disponíveis na literatura procedeu-se à identificação do sistema em causa. O modelo desenvolvido foi utilizado para estabelecer um ambiente de simulação e desenho de controladores e assim, desenvolver um controlador preditivo baseado em modelo para controlar a temperatura dentro do gasificador. O modelo desenvolvido apresenta um grande potencial como modelo de predição, apesar da deterioração do seu desempenho quando usado como simulador. O controlador desenvolvido foi capaz de estabilizar a saída gerada pelo modelo de simulação para todos os set-points testados. O trabalho desenvolvido constitui uma base de trabalho bastante completa que deverá facilitar desenvolvimentos futuros.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Automated, computational approaches to kinetic model and parameter determination

A major bottleneck in the transition from chemistry research at lab scale to process development is a lack of quantitative chemical synthesis information. Critical aspects of this information include knowing the correct reaction model and precise kinetic parameters. If this information is available, classical reaction engineering principles may be utilised to shorten process development times and lower costs. Identifying the correct reaction model for a particular process, however, can be challenging and time-consuming, particularly for physical-organic chemists and kinetics experts that may be busy with other aspects of process development. The work presented herein describes computational approaches that automatically determine the most likely kinetic model and associated parameters based on the experimental data supplied, without expert chemical intuition. The concept for these methodologies involves a comprehensive model evaluation tool. The experimental data and the species involved in the process are inputted. Based on mass balance, all mass-balance-allowed transformations between these species are identified. All possible models are then compiled from this list of transformations, featuring unique combinations of these model terms. Every model is then evaluated using ordinary differential equation (ODE) solvers and optimisation algorithms to maximise the convergence of simulated reaction progression with the experimental data, thereby identifying the kinetic parameters. Each model is then statistically evaluated to determine which model is the most likely to be correct. Using these methodologies allows any chemist to automatically determine a reaction model and kinetic constants for a particular system, by performing all kinetic analysis autonomously. Their most expensive resource, time, can then be focussed on other tasks that cannot be automated