Le développement de nouveaux catalyseurs pour l’hydrogénation sélective du propyne et du propadiène (MAPD) est un processus complexe, puisqu’il s’agit d’une réaction rapide effectuée en gaz-liquide-solide. Dans ces conditions, le flux d'hydrogène transporté aux sites actifs du catalyseur contrôle la vitesse de la réaction, particulièrement à l’échelle pilote. Cela rend difficile la comparaison des performances des différents catalyseurs (conversion et sélectivité). Afin d’améliorer la discrimination des solides, l’hydrogénation sélective du MAPD a été étudiée en monophasique (fluide/solide) dans un réacteur filaire à haute pression et en supercritique.La première partie de la thèse a eu pour objectif de déterminer les conditions de fonctionnement adéquates : un dispositif expérimental microfluidique et une méthodologie associée ont été développés et validés pour obtenir les diagrammes P-T de miscibilité et les coordonnées critiques des systèmes réactionnels mis en jeu. En parallèle, le réacteur a été caractérisé en utilisant des outils numériques (CFD) appliqués à l’hydrodynamique et au transfert de masse. Les tests expérimentaux ont alors pu être menés, dans la seconde partie de la thèse, afin d’étudier l'hydrogénation du MAPD à 303 K entre 20 et 120 bar. Dans ces conditions, plusieurs paramètres ont été étudiés, tels que la PPH (vitesse spatiale horaire, ou WHSV en anglais), la pression et la fraction de solvant. Les résultats montrent un gain important de conversion du MAPD à haute pression et en conditions supercritiques par rapport aux conditions classiques (>5 fois plus). Cela peut s’expliquer par la suppression de l’interface gaz-liquide et l’amélioration des diffusivités. Les variations de sélectivité observées en parallèle montre sa dépendance au flux d’hydrogène amené. Ces résultats prometteurs permettent une meilleure discrimination des catalyseurs ainsi qu’une meilleure compréhension du système réactif. Ainsi, pour la première fois, en utilisant ces données non classiques, il a au final été possible d'estimer des paramètres cinétiques intrinsèques pour l’hydrogénation sélective des coupes C3. / The development of new catalysts for propyne and propadiene (MAPD) hydrogenation is a complex process, because it is a fast reaction performed in gas-liquid-solid. Indeed, in these conditions, the hydrogen flux (G/L and L/S) transported to the reaction sites controls the overall reaction rate, particularly at pilot scale. To avoid this limitation, the MAPD selective hydrogenation was performed in single-phase, using a single pellet string reactor (SPSR) at high-pressure and supercritical conditions. For both conditions, the literature is scarce. Thus, the first step was to develop and validate a microfluidic experimental apparatus and a methodology based on “design of experiments”, in order to obtain PT miscibility diagrams and critical coordinates. These methods combined allowed a fast PT screening compared to conventional phase behavior cells, being around 5 times higher. In parallel, the SPSR was characterized by computational fluid dynamics (CFD) for flow and mass transfer. It was shown that the hydrodynamic inside the reactor can be modeled as a plug flow reactor with low axial dispersion, and a LS mass transfer correlation was proposed. After the fluid and reactor characterization, the MAPD hydrogenation was performed at 303 K and from 20 to 120 bar. At these conditions, several parameters were tested, such as WHSV (weight hourly space velocity), pressure and solvent fraction. The results showed that high-pressure and supercritical conditions offer better reaction performance, which is due to the suppression of the gas-liquid limitation and to the diffusivity enhancements (more than 5 times faster than conventional conditions). With this thesis, it was possible, for the first time, to estimate the intrinsic kinetics parameters of a dense C3 cut mixture hydrogenation, allowing a deeper understanding of the involved mechanism. Thus, the use of unconventional conditions has opened a door to new forms of catalyst screening and new ways to study kinetics.

Submitted by Uillis de Assis Santos (uillis.assis@ufba.br) on 2018-01-26T13:26:54Z No. of bitstreams: 1 AnaRosaCaribédeGóesMassa_Dissertação-UFBA-Politécnica-EngenhariaIndustrial-2017.pdf: 4582890 bytes, checksum: 3c5c6099462e9b7f61ff397081c5dd6a (MD5) / Approved for entry into archive by Vanessa Reis (vanessa.jamile@ufba.br) on 2018-01-26T16:03:46Z (GMT) No. of bitstreams: 1 AnaRosaCaribédeGóesMassa_Dissertação-UFBA-Politécnica-EngenhariaIndustrial-2017.pdf: 4582890 bytes, checksum: 3c5c6099462e9b7f61ff397081c5dd6a (MD5) / Made available in DSpace on 2018-01-26T16:03:46Z (GMT). No. of bitstreams: 1 AnaRosaCaribédeGóesMassa_Dissertação-UFBA-Politécnica-EngenhariaIndustrial-2017.pdf: 4582890 bytes, checksum: 3c5c6099462e9b7f61ff397081c5dd6a (MD5) / Analisadores em linha fornecem uma resposta rápida de composição em comparação às análises laboratoriais. Porém, esses estão sujeitos a frequentes interferências e contaminações devido às substâncias utilizadas nas correntes reais, que agridem, contaminam e comprometem o funcionamento do equipamento, exigindo manutenções rotineiras. Durante estas, há perda de informações vitais que podem culminar numa parada da produção, a não ser que outro equipamento permita estimar tais informações de maneira confiável. Desta forma, o presente trabalho tem por objetivo desenvolver um analisador virtual para estimar a concentração dos contaminantes metilacetileno e propadieno (MAPD) em um reator trickle bed em uma indústria de propileno no Brasil. A partir da coleta de dados de processos de uma campanha catalítica, coletados por cromatógrafos a gás, termopares e medidores de vazão, foram desenvolvidos modelos de calibração multivariada utilizando a técnica de Regressão por Mínimos Quadrados Parciais (PLS), para dois leitos catalíticos, A e B. Dados de treze variáveis de processo, monitoradas a cada 10 minutos durante uma campanha catalítica para cada leito, foram utilizados. Os modelos PLS foram desenvolvidos e validados e foram capazes de fornecer valores preditos confiáveis, com R2 de 0,84 para o leito A e 0,92 para o leito B. Normalidade e homocedacidade dos resíduos foram observadas em ambos modelos. Além disso, foi realizada uma seleção de variáveis utilizando o gráfico de escores VIP (Variable Importance in Projection) obtido durante o desenvolvimento dos modelos PLS. As variáveis mais importantes foram selecionadas e os modelos PLS construídos apenas com essas variáveis mantiveram a capacidade de predição em ambos os leitos, com valores de R2 de 0,82 para o leito A e 0,87 para o leito B. Normalidade e homocedacidade dos resíduos foram mantidas, e um teste F não gerou evidência que indicasse diferença significativa entre os modelos desenvolvidos antes e após a seleção de variáveis. Dessa forma, os modelos PLSVIP fornecem uma estimativa confiável do teor de MAPD no reator trickle bed na planta de propeno estudada. Esses resultados mostraram que os métodos desenvolvidos possuem um alto potencial de aplicação nos reatores estudados caso haja necessidade, evitando assim uma parada da planta e subsequente perda de capital investido. / Online analysers grant a faster answer on the composition of products when compared with laboratory analysis. However, the former is often affected by substances in the stream line which harm and compromise its normal working state, calling for frequent maintenance. During those, the loss of vital information could lead to a halt in production, unless another device allows for such information to be carefully estimated.As such, this paper aims at developing a Virtual Analyser that can estimate the concentration of methylacetylene and propadiene (MAPD) contaminants in a trickle bed reactor at a propene industrial plant in Brazil. Process data collected in the reactor by gas chromatographers,temperature probes and flowmeters were employed to build multivariate calibration models by using the Partial Least Square Regression(PLS)technique, for two bed reactors, A and B.Data from thirteen process variables, monitored every 10 minutes during one catalytic campaign for each bed, of about three months each, were used. The developed PLS models for both beds have shown a great prediction capacity and remarkable performances, with R2 of 0.84 for bed A and 0.92 for bed B. Residual normality and homoscedasticity were observed for both models. In addition, a variable selection approach was carried out using the VIP (Variable Importance in Projection) score plot obtained during the developed PLS models. The most important variables (process variables)were selected and the PLS models built with only these variables were still able to keep are markable prediction ability for both beds, with a R2 of 0.82 for bed A and 0.87 for bed B. Residual normality and homoscedasticity were kept, and an F test did not provide evidence for significant difference between the models developed before and after the variable selection. Therefore, the PLS-VIP models provided a reliable estimate of the MAPD content in the trickle bed reactors at the studied propene plant. These outcomes showed that the developed methods present a high potential for application in the studied reactors, if necessary, in order to prevent a halt in production and its subsequent loss of invested capital.

Throughout today’s society, increasingly more areas are being automated. Grocery stores however have been the same for years. Only recently, self-checkout counters and online shopping have been utilised in this business area. This thesis aims to take it to the next step by introducing automated grocery stores using a multi-agent system. Orders will be given to the system, and on a small area, multiple agents will pick the products in a time-efficient way and deliver them to the customer. This can both increase the throughput but also decrease the food waste and energy consumption of grocery stores. This thesis investigates already existing solutions for the multi-agent pickup and delivery problem. It extends these to the important case of batched tasks in order to improve the customer experience. Batches of tasks represent shopping carts, where fast completion of whole batches gives greater customer satisfaction. This notion is not mentioned in related work, where completion of single tasks is the main goal. Because of this, the existing solution does not accommodate the need of batches or the importance of completing whole batches fast and in somewhat linear order. For this purpose, a new metric called batch ordering weighted error (BOWE) was created that takes these factors into consideration. Using BOWE, one existing algorithm has been extended into prioritizing completing whole batches and is now called B-PIBT. This new algorithm has significantly improved BOWE and even batch service time for the algorithm in key cases and is now superior in comparison to the other state-of-the-art algorithms.