488 research outputs found

    Computer-aided modeling for efficient and innovative product-process engineering

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    Model baserede computer understøttet produkt process engineering har opnået øget betydning i forskelligste industrielle brancher som for eksampel farmaceutisk produktion, petrokemi, finkemikalier, polymerer, bioteknologi, fødevarer, energi og vand. Denne trend er forventet at fortsætte på grund af substantielle fordele, hvilke computer understøttede metoder medfører. Den primære forudsætning af computer understøttet produkt process engineering erselvfølgelig den tilgængelighed af modeller af forskellige typer, former og anvendelser. Udviklingen af den påkrævet modellen for de undersøgte systemer er normalt en tidskrævende udfordring og derfor mest også dyrt. Den involverer forskelligste trin, fagekspert viden og dygtighed og forskellige modellerings værktøjer. Formålet af dette projekt er at systematisere den model udviklings proces og anvendelse og dermed øge effektiviteten af modeller såvel somkvaliteten. Den væsentlige bidrag af denne PhD afhandling er en generisk metodologi for proces model udviklingen og anvendelse i kombination med grundige algoritmiske arbejdes diagrammer for de forskellige involverede modeller opgaver og udviklingen af computer understøttede modeller rammer hvilke er strukturbaseret på den generiske metodologi, delvis automatiseret i de forskellige arbejdstrin og kombinerer alle påkrævet værktøjer, understøttelseog vejledning for de forskellige arbejdstrin. Understøttede modelleringsopgaver er etableringen af modeller mål, indsamling af de nødvendige informationer, model formulering inklusive numeriske analyser, etablering af løsningsstrategier og forbinding med den passende løsningsmodul, model identificering og sondering såvel som model anvendelse for simulation og optimering. Den computer understøttede modeller ramme blev implementeret i en brugervenlig software. En række forskellige demonstrationseksempler fra forskellige områder i kemisk ogbiokemiske engineering blev løst for udvikling og validering af den generiske modellerings metodologi og den computer understøttet modeller ramme anvendt på den udviklet software værktøj.Model-based computer aided product-process engineering has attained increased importance in a number of industries, including pharmaceuticals, petrochemicals, fine chemicals, polymers, biotechnology, food, energy and water. This trend is set to continue due to the substantial benefits computer-aided methods provide. The key prerequisite of computer-aided productprocess engineering is however the availability of models of different types, forms andapplication modes. The development of the models required for the systems under investigation tends to be a challenging, time-consuming and therefore cost-intensive task involving numerous steps, expert skills and different modelling tools. The objective of this project is to systematize the process of model development and application thereby increasing the efficiency of the modeller as well as model quality.The main contributions of this thesis are a generic methodology for the process of model development and application, combining in-depth algorithmic work-flows for the different modelling tasks involved and the development of a computer-aided modelling framework. This framework is structured, is based on the generic modelling methodology, partially automates the involved work-flows by integrating the required tools and, supports and guides the userthrough the different work-flow steps. Supported modelling tasks are the establishment of the modelling objective, the collection of the required system information, model construction including numerical analysis, derivation of solution strategy and connection to appropriate solvers, model identification/ discrimination as well as model application for simulation and optimization. The computer-aided modelling framework has been implemented into an userfriendlysoftware.A variety of case studies from different areas in chemical and biochemical engineering have been solved to illustrate the application of the generic modelling methodology, the computeraided modelling framework and the developed software tool

    Scaleup and hydrodynamics study of gas-solid spouted beds

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    A thorough understanding of the complex flow structure of gas-solid spouted bed is crucial for design, scale-up and performance. Advanced gas-solid optical probes were developed and used to evaluate different hydrodynamic parameters of spouted beds. These optical probes measure solids concentration, velocity and their time series fluctuations. Since solids concentration needs to be converted to solids holdup through calibration, for meaningful interpretation of results, a novel calibration method was proposed (which is inexpensive and reliable compared to the current reported methods) and validated in the present study. The reported dimensionless groups approach of spouted bed scale-up was assessed and was found that the two different spouted beds were not hydrodynamically similar. Hence, a new scale-up methodology based on maintaining similar or close radial profiles of gas holdup was proposed, assessed and validated. CFD was used after it was validated as an enabling tool to facilitate the implementation of the newly developed scale-up methodology by identifying the new conditions for maintaining radial profiles of gas holdup while scaling up. It can also be implemented to quantify the effect of various variables on their hydrodynamic parameters. Gamma Ray Densitometry (GRD), a non-invasive radioisotope based technique, was developed and demonstrated to montior [sic]on-line the conditions for the scale-up, flow regime and spouted beds operation. The solids holdup in spout region increases with axial height due to movement of solids from the annulus region. However, solids velocity in the spout region decreases with axial height. In the annulus region the solids move downward as a loose packed bed and the solids velocity and holdup do not change with axial height. Using factorial design of experiments it was found that solids density, static bed height, particle diameter, superficial gas velocity and gas inlet diameter had significant effect on the identification of spout diameter. Flow regimes in spouted bed were determined with the help of optical probes, pressure transducers and GRD. It was found that the range of stable spouting regime is higher in 0.152 m beds and the range of stable spouting decreases in the 0.076 m beds. The newly developed non-invasive radioisotope technique (GRD) was able to successfully identify different flow regimes and their transition velocities besides scale-up conditions and operation --Abstract, page iii

    Neural networks in multiphase reactors data mining: feature selection, prior knowledge, and model design

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    Les réseaux de neurones artificiels (RNA) suscitent toujours un vif intérêt dans la plupart des domaines d’ingénierie non seulement pour leur attirante « capacité d’apprentissage » mais aussi pour leur flexibilité et leur bonne performance, par rapport aux approches classiques. Les RNA sont capables «d’approximer» des relations complexes et non linéaires entre un vecteur de variables d’entrées x et une sortie y. Dans le contexte des réacteurs multiphasiques le potentiel des RNA est élevé car la modélisation via la résolution des équations d’écoulement est presque impossible pour les systèmes gaz-liquide-solide. L’utilisation des RNA dans les approches de régression et de classification rencontre cependant certaines difficultés. Un premier problème, général à tous les types de modélisation empirique, est celui de la sélection des variables explicatives qui consiste à décider quel sous-ensemble xs ⊂ x des variables indépendantes doit être retenu pour former les entrées du modèle. Les autres difficultés à surmonter, plus spécifiques aux RNA, sont : le sur-apprentissage, l’ambiguïté dans l’identification de l’architecture et des paramètres des RNA et le manque de compréhension phénoménologique du modèle résultant. Ce travail se concentre principalement sur trois problématiques dans l’utilisation des RNA: i) la sélection des variables, ii) l’utilisation de la connaissance apriori, et iii) le design du modèle. La sélection des variables, dans le contexte de la régression avec des groupes adimensionnels, a été menée avec les algorithmes génétiques. Dans le contexte de la classification, cette sélection a été faite avec des méthodes séquentielles. Les types de connaissance a priori que nous avons insérés dans le processus de construction des RNA sont : i) la monotonie et la concavité pour la régression, ii) la connectivité des classes et des coûts non égaux associés aux différentes erreurs, pour la classification. Les méthodologies développées dans ce travail ont permis de construire plusieurs modèles neuronaux fiables pour les prédictions de la rétention liquide et de la perte de charge dans les colonnes garnies à contre-courant ainsi que pour la prédiction des régimes d’écoulement dans les colonnes garnies à co-courant.Artificial neural networks (ANN) have recently gained enormous popularity in many engineering fields, not only for their appealing “learning ability, ” but also for their versatility and superior performance with respect to classical approaches. Without supposing a particular equational form, ANNs mimic complex nonlinear relationships that might exist between an input feature vector x and a dependent (output) variable y. In the context of multiphase reactors the potential of neural networks is high as the modeling by resolution of first principle equations to forecast sought key hydrodynamics and transfer characteristics is intractable. The general-purpose applicability of neural networks in regression and classification, however, poses some subsidiary difficulties that can make their use inappropriate for certain modeling problems. Some of these problems are general to any empirical modeling technique, including the feature selection step, in which one has to decide which subset xs ⊂ x should constitute the inputs (regressors) of the model. Other weaknesses specific to the neural networks are overfitting, model design ambiguity (architecture and parameters identification), and the lack of interpretability of resulting models. This work addresses three issues in the application of neural networks: i) feature selection ii) prior knowledge matching within the models (to answer to some extent the overfitting and interpretability issues), and iii) the model design. Feature selection was conducted with genetic algorithms (yet another companion from artificial intelligence area), which allowed identification of good combinations of dimensionless inputs to use in regression ANNs, or with sequential methods in a classification context. The type of a priori knowledge we wanted the resulting ANN models to match was the monotonicity and/or concavity in regression or class connectivity and different misclassification costs in classification. Even the purpose of the study was rather methodological; some resulting ANN models might be considered contributions per se. These models-- direct proofs for the underlying methodologies-- are useful for predicting liquid hold-up and pressure drop in counter-current packed beds and flow regime type in trickle beds

    A Novel Method for Pre-combustion CO2 Capture in Fluidized Bed

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    La comunidad internacional está realizando enormes esfuerzos para mitigar los efectos de las emisiones de gases de efecto invernadero (GEI) en el cambio climático. Aproximadamente le 25% de las emisiones globales de GEI (fundamentalmente CO2) son generados por la combustión de combustibles fósiles en el sector eléctrico. La captura y almacenamiento de CO2 se ha propuesto como una alternativa para reducir las emisiones de GEI en centrales térmicas. Numerosas tecnologías para la captura de CO2 se han desarrollado en los últimos años, fundamentalmente en tres líneas tecnológicas: postcombustión, oxicombustión y precombustión. Esta tesis presenta un nuevo método para la captura de CO2 en precombustión, produciendo hidrógeno a partir de carbón, sin emisiones de GEI. El objetivo principal de este trabajo ha sido desarrollar un modelo completo, mediante herramientas de fluido dinámica computacional (CFD), del proceso de reformado de un gas de síntesis con alto contenido en metano combinado con la captura de CO2 mediante adsorción con sorbentes sólidos regenerables. Este proceso es conocido como reformado de metano mejorado por adsorción (o SE-SMR, su acrónimo en inglés). SE-SMR representa una novedosa y eficiente energéticamente ruta para la producción de hidrógeno con captura in situ de CO2. Este proceso ha sido estudiado en un lecho fluido burbujeante, usando sorbentes sólidos de óxido de calcio como captores de CO2. Dos sorbentes sólidos han sido estudiados en laboratorio: uno natural (Dolomita) y uno sintético (CaO- Ca12Al14O33). Además, varios tratamientos han sido desarrollados para mejorar la capacidad de captura de estos sorbentes. Un completo modelo CFD del proceso de SE-SMR ha sido desarrollado. Una aproximación Euleriana-Euleriana ha sido combinada con la Teoría Cinética de Flujos Granulares para simular la fluidodinámica del lecho fluido burbujeante. Los reacciones químicas de reformado y carbonatación han sido implementadas en el modelo CFD. Se ha incluido un modelo detallado de captura de CO2 para simular el comportamiento de los diferentes sorbentes sometidos a diferentes pretratamientos para mejorar su rendimiento. Asimismo, un modelo de arrastre de partículas ha sido desarrollado para reducir el coste computacional de las simulaciones a escala semi-industrial. Se ha llevado a cabo una extensa campaña de simulaciones para validar el modelo a escala de laboratorio y semi-industrial. Las simulaciones CFD han sido combinadas con un Diseño de Experimentos Robusto, con el objetivo predecir y evaluar la sensibilidad del proceso SE-SMR a diversos factores operativos

    IMPROVING JET ATTRITION IN FLUIDIZED BEDS

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    Fluidized bed reactors are used extensively in many industrial applications due to attractive features such as good solids and gases mixing, and rapid heat and mass transfer. Fluid Coking is a process that utilizes these attractive properties. It is a non-catalytic thermal conversion process that is used to upgrade bitumen from oil sands in order to produce synthetic crude oil. Particle size control is crucial in Fluid Coking in order to maintain a well fluidized bed and a satisfactory production rate. Therefore, steam is injected through supersonic nozzles in the reactor section of the Fluid Coker, to attrit the coke particles and maintain the desired particle size distribution. Currently, a large quantity of steam is used by the Coker attrition nozzles. If the steam consumption of the attrition nozzles could be reduced, it would reduce the energy consumption and lead to a higher reactor throughput. This is the primary research objective for this thesis work. The first portion of the research work was focused on the optimization of supersonic nozzle operating conditions, in terms of maximizing the grinding efficiency to minimize the flowrate of attrition gas. The attrition nozzle operating pressure, attrition time, and nozzle scale were tested to determine their effect on the grinding efficiency. Attrition gas consumptions were compared for the same new surface area created in order to find the optimal operating conditions, for which a minimum flowrate of attrition gas is used. The effect of fluid bed hydrodynamics on jet attrition was investigated next. A specially designed fluidized bed was used to create two hydrodynamics zones, where the superficial gas velocity could be independently adjusted. Supersonic attrition jets were tested under different hydrodynamic conditions, with different nozzle penetrations where the attrition jet could either straddle both hydrodynamic zones, or be completely enclosed within one hydrodynamic zone. Local bed pressure gradient was measured along the width of the bed to help explain the effect of bed hydrodynamics on jet attrition. Finally, the effect of the nozzle inclination angle on jet attrition was studied. A supersonic nozzle was used and able to adjust from 0° to 90°. The optimal nozzle inclination angle was found, which generated the largest new surface area. Particle size distribution analysis was carried out to determine the amount of coarse particles ground and fine particles generated for each nozzle angle

    Mass Transfer in Multiphase Systems and its Applications

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    This book covers a number of developing topics in mass transfer processes in multiphase systems for a variety of applications. The book effectively blends theoretical, numerical, modeling and experimental aspects of mass transfer in multiphase systems that are usually encountered in many research areas such as chemical, reactor, environmental and petroleum engineering. From biological and chemical reactors to paper and wood industry and all the way to thin film, the 31 chapters of this book serve as an important reference for any researcher or engineer working in the field of mass transfer and related topics

    Particle Attrition with Supersonic Nozzles in a High Temperature Fluidized Bed

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    Fluidized beds are widely used for a variety of processes such as food, pharmaceutical, petrochemical and energy production. As a typical application of fluidized beds, the fluid coking process uses thermal cracking reactions to upgrade heavy oils and bitumen from oil sands. In order to maintain a well fluidized bed and a satisfactory operation, a series of supersonic nozzles are used to inject high pressure steam in the bed to maintain the coke particle within an optimal range. Currently, the attrition nozzles consume a large florwrate of high pressure and superheated steam, which accounts for about 40 % of the total energy consumption in fluid coking reactors. Improving the efficiency of the attrition process would increase energy efficiency and reduce sour waste water production, reducing the environmental impact of heavy oil upgrading. Therefore, the main objective of the present thesis is an experimental and numerical study of particle attrition with supersonic nozzles in high temperature fluidized beds. The specific objective is to improve particle grinding efficiency and reduce the steam consumption in the fluid coking process. To achieve the research objective, the primary investigations focused on the solids entrainment and penetration of jets issuing from supersonic nozzles, which have significant effects on particle attrition. Novel measuring techniques, therefore, were developed to accurately measure the flowrate of solids entrained into the jet and its penetration length. The numerical and experimental studies reveal that the jet penetration lengths are related to the two-phase Froude number. A new correlation was developed to predict the penetration length of jets issuing from supersonic nozzles in high temperature fluidized beds, based on Benjelloun’s correlation and the Froude number. The attrition experimental results demonstrate that larger scale nozzles, operating with a high flowrate of a low molecular weight gas at high temperature provide the highest grinding efficiency. A jet-induced attrition model in fluidized beds at high temperature has been proposed and developed. The model is a coupled Eulerian-Eulerian multiphase model with a population balance method. The particle-particle interactions are described with the kinetic theory of granular flow. Experimental results were used to determine and modify the critical parameters of the model. The best prediction was obtained using the Ghadiri breakage kernel, generalized daughter size distribution function, and discrete solution method. Finally, the research focused on the enhancement of jet-induced attrition in fluidized bed. A twin-jet nozzle gave a grinding efficiency that is about 35% higher than with a single nozzle. The benefits of the twin-jet nozzle seem stronger at higher nozzle pressures and high temperature. It is likely that the twin-jet nozzle entrains more solids into the jets when compared with a single nozzle with the same gas flowrate

    Catalytic fast pyrolysis of biomass

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    Utilization of biomass offers a potential to sustain the current petro-chemical economy for the production of chemicals and (transportation) fuels on basis of renewable resources. Crude bio-oil derived from fast pyrolysis of lignocellulosic biomass is a mixture of water (15-30 wt.%) and various oxygen containing organic compounds. The presence of oxygen in bio-oils (ca. 35–40 wt.%) is commonly believed to be the origin of problems caused by its high water content (15–30 %), corrosiveness (pH of 2–3), relatively low heating value compared to fossil fuels (ca. 17 MJ/kg), poor volatility, and high viscosity (35–1000 cP at 40 °C). However, not only the level of oxygen in the bio-oil is too high, but also the way it exists (functionality) is a part of the problem. Improving the quality of the bio-oils, whether or not in combination with a certain degree of oxygen removal, would include a selective transformation of certain oxygen functionalities such as acids and aldehydes into ‘desired’ or acceptable ones like alcohols, phenols, and ethers. Application of heterogeneous catalysis in fast pyrolysis (i.e. catalytic fast pyrolysis; CFP) may lead to a liquid product (i.e. catalytic fast pyrolysis oil, CFP-oil) with an improved quality compared to that of crude bio-oil. Here, the improvement in bio-oil quality refers to the production of either high yields of transportation fuel compounds (e.g. aromatics, olefins) and specialty chemicals (e.g. phenolics), or just a drop-in refinery feedstock to be blended with the feed streams of existing petroleum refineries. While the literature on catalytic fast pyrolysis of biomass -mainly focussed on catalyst screening- is rapidly expanding, there is an urgent need for the translation of laboratory results to viable process concepts and bench/pilot plant trials. Together with the development of efficient catalysts, the design and the intensification of the process with efficient heat integration are of significant importance in the catalytic conversion of lignocellulosic biomass to the targeted liquid product. The present thesis discusses the catalytic fast pyrolysis of lignocellulosic biomass in a process oriented way that may initiate a useful process technology development in the near future. The final goal is to come up with recommendations and suggestions on how to realize this technique at a commercial/industrial scale. That requires a better understanding of the precise effects of the essential process parameters (e.g. processing mode; in- or ex situ) and design elements (e.g. reactor type, catalyst type) on the one hand, and definitions and outcomes of possible obstacles (e.g. successive regeneration of the catalyst, effect of biomass ash) on the other. In this work, two types of continuously operated (catalytic) fast pyrolysis reactors were used, viz. an auger reactor and a mechanically stirred bed reactor. In all experiments performed in both setups, pine wood with a particle size range of 1 to 2 mm was pyrolyzed at a constant reactor temperature of 500 °C. In the auger reactor, first the effect of the operation mode on the product yields and compositions has been investigated while using a single type of heterogeneous ZSM-5 based acidic catalyst. Two operation modes were tested. In situ operation includes the mixing of biomass and catalyst inside a single reactor, while ex situ refers to catalytic treatment of the pyrolysis vapours in a secondary reactor. A second study was concerned with the screening of various heterogeneous catalysts (and their metal doped counterparts) in in situ operation. In all experiments, the presence of catalysts led to the production of additional water, coke and gases at the expense of the liquid organics and char. The overall performance of in situ catalysis in terms of oil quality was considerably better than that of ex situ catalysis; more aromatics and phenols were produced in the case of in situ operation. That may be caused by different vapour residence times and vapour-catalyst contact times. Among all eight catalysts tested, the acidic catalyst containing some redox active metal, the basic catalyst with a mixture of two metal oxides (calcined), and a metal oxide doped gamma-alumina catalyst (calcined) were found to be the best performing ones, based on both the deoxygenation requirements and the production of desirable compounds in high yields. In the mechanically stirred bed reactor, we studied i) the effect of a repeated catalyst regeneration (eight cycles in total), and ii) the effects of the pine wood ash on the yields and composition of the products. In all catalytic experiments, a single type of a ZSM-5 based catalyst was used in situ. Along the reaction/regeneration cycles, trends in pyrolysis product yields converging to that of non-catalytic levels were observed. This revealed that the activity, and thus the influence of the catalyst slowly declined, which was confirmed by a BET surface area reduction of 63 %. Ash concentrations as low as ca. 3 wt.% relative to the amount of pine wood fed, and ca. 0.002 wt.% relative to the amount of bed material, were found sufficient to affect the yield and composition of the CFP products unfavourably. Finally, the technical and operational barriers for the implementation of catalytic fast pyrolysis technology are discussed while focusing on the process modes and parameters, economical use of the primary and secondary products, and heat integration. Some process alternatives for an efficient CFP operation are suggested as well. Research has, until now, been focused mainly on screening and small-scale testing of various catalysts. One challenge in developing CFP of biomass is the design and large scale production of such catalysts to enable testing in continuously operated, bench and pilot scale installations. FCC type of catalysts are the only suitable ones commercially available. But they are developed especially for use in a riser reactor and short contact times (differing significantly from typical biomass devolatilization times). The main problem in CFP of biomass was found to be the presence of the biomass originated alkaline ash which eventually poisons any catalyst in case of direct contact. In a commercial process, a solution may be to separate the biomass fast pyrolysis from the catalytic treatment of the vapours (i.e. ex situ processing mode) where the physical contact between the biomass minerals and the catalyst is excluded. Even though this requires significant process adjustments, ex-situ processing allows the catalyst to be re-used in a much larger number of reaction/regeneration cycles than in case of in situ operation

    Enhanced Hydrogen Production in Integrated Catalytic Adsorption (ICA) Steam Gasification System Utilizing Palm Kernel Shell

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    Energy crises and serious environmental issues associated with fossil fuels urge for alternative, sustainable and renewable energy. Hydrogen has a potential to be a significant energy carrier in the future since it is a clean fuel. Hydrogen production from local biomass i.e. palm oil waste is an attractive option due to its abundance in the country. Biomass catalytic steam gasification and steam gasification with in-situ CO2 adsorption processes show great potential for renewable hydrogen production. However, the quality and quantity of hydrogen rich gas with considerable tar inhibits the application of these processes in power generation and fuel cell
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