Tesis sobre el tema "Thermodynamic Equilibrium Calculations"

Les simulations numériques sont un outil puissant pour analyser les systèmes dynamiques, mais peuvent être coûteuses en termes de calcul et prendre beaucoup de temps pour les systèmes complexes à haute résolution. Au cours des dernières décennies, les chercheurs se sont efforcés d'accélérer les simulations numériques grâce à des améliorations algorithmiques et au calcul haute performance (HPC). Plus récemment, l'intelligence artificielle (IA) pour la science est en plein essor et implique l'utilisation de techniques d'IA, spécifiquement l'apprentissage automatique et l'apprentissage profond, pour résoudre des problèmes scientifiques et accélérer les simulations numériques, ayant le potentiel de révolutionner un large éventail de domaines. L'objectif principal de cette thèse est d'accélérer les calculs d'équilibre thermodynamique au moyen de techniques utilisées pour accélérer les simulations numériques. Les calculs d'équilibre thermodynamique sont capables d'identifier les phases des mélanges et leurs compositions à l'équilibre et jouent un rôle crucial dans de nombreux domaines, tels que le génie chimique et l'industrie pétrolière. Nous atteignons cet objectif sous deux aspects. D'une part, nous utilisons des cadres d'apprentissage profond pour réécrire et vectoriser les algorithmes impliqués dans les calculs d'équilibre thermodynamique, facilitant l'utilisation de matériel divers pour le HPC. D'autre part, nous utilisons des réseaux neuronaux pour remplacer les sous-routines longues et répétitives des calculs d'équilibre thermodynamique, ce qui est une technique largement adoptée de l'IA pour la science. Un autre point central de cette thèse est de relever le défi de la généralisation de domaine (DG) dans la classification d'images. La DG implique l'entraînement de modèles sur des domaines connus qui peuvent efficacement se généraliser à des domaines inconnus, ce qui est crucial pour le déploiement de modèles dans des applications réelles critiques pour la sécurité. La DG est un domaine de recherche actif en apprentissage profond. Bien que diverses méthodes DG aient été proposées, elles nécessitent généralement des étiquettes de domaine et manquent d'interprétabilité. Par conséquent, nous visons à développer un nouvel algorithme DG qui ne nécessite pas d'étiquettes de domaine et est plus interprétable
Numerical simulations are a powerful tool for analyzing dynamic systems, but can be computationally expensive and time-consuming for complex systems with high resolution. Over the past decades, researchers have been striving to accelerate numerical simulations through algorithmic improvements and high-performance computing (HPC). More recently, artificial intelligence (AI) for science is on the rise and involves using AI techniques, specifically machine learning and deep learning, to solve scientific problems and accelerate numerical simulations, having the potential to revolutionize a wide range of fields. The primary goal of this thesis is to speed up thermodynamic equilibrium calculations by means of techniques used to accelerate numerical simulations. Thermodynamic equilibrium calculations are able to identify the phases of mixtures and their compositions at equilibrium and play a pivotal role in many fields, such as chemical engineering and petroleum industry. We achieve this goal from two aspects. One the one hand, we use deep learning frameworks to rewrite and vectorize algorithms involved in thermodynamic equilibrium calculations, facilitating the use of diverse hardware for HPC. On the other hand, we use neural networks to replace time-consuming and repetitive subroutines of thermodynamic equilibrium calculations, which is a widely adopted technique of AI for science. Another focus of this thesis is to address the challenge of domain generalization (DG) in image classification. DG involves training models on known domains that can effectively generalize to unseen domains, which is crucial for deploying models in safety-critical real-world applications. DG is an active area of research in deep learning. Although various DG methods have been proposed, they typically require domain labels and lack interpretability. Therefore, we aim to develop a novel DG algorithm that does not require domain labels and is more interpretable

In this thesis point defects in semiconductors are studied by electronic structure calculations. Results are presented for the stability and equilibrium concentrations of native defects in GaP, InP, InAs, and InSb, for the entire range of doping conditions and stoichiometry. The native defects are also studied on the (110) surfaces of InP, InAs, and InSb. Comparing the relative stability at the surface and in the bulk, it is concluded that the defects have a tendency to migrate to the surface. It is found that the cation vacancy is not stable, but decomposes into an anion antisite-anion vacancy complex. The surface charge accumulation in InAs is explained by complementary intrinsic doping by native defects and extrinsic doping by residual hydrogen. A technical investigation of the supercell treatment of defects is performed, testing existing correction schemes and suggesting a more reliable alternative. It is shown that the defect level of [2VCu-IIICu] in the solarcell-material CuIn1-xGaxSe2 leads to a smaller band gap of the ordered defect γ-phase, which possibly explains why the maximal efficiency for CuIn1-xGaxSe2 has been found for x=0.3 and not for x=0.6, as expected from the band gap of the α-phase. It is found that Zn diffuses via the kick-out mechanism in InP and GaP with activation energies of 1.60 eV and 2.49 eV, respectively. Explanations are found for the tendency of Zn to accumulate at pn-junctions in InP and to why a relatively low fraction of Zn is found on substitutional sites in InP. Finally, it is shown that the equilibrium solubility of dopants in semiconductors can be increased significantly by strategic alloying. This is shown to be due to the local stress in the material, and the solubility in an alloy can in fact be much higher than in either of the constituting elements. The equilibrium solubility of Zn in Ga0.9In0.1P is for example five orders of magnitude larger than in GaP or InP.

Military aircraft that require high maneuverability, durability, ballistic protection, reparability, and energy efficiency require structural alloys with low density, high toughness, and high strength. Also, repairs to these aircraft demand a production process that has the flexibility to be relatively in-situ with the same high-performance output. Materials produced by the cold spray process, a thermo-mechanical powder consolidation technique, meet many of the requirements. In accordance with President Obama’s 2011 Materials Genome Initiative, the focus of this effort is to design customized aluminum alloy powders which exploit the unique behavior and properties of the materials created by the cold spray process. Analytical and computational models are used to customize microchemistry, thermal conditioning, and solidification behavior of the powders by predicting equilibrium and non-equilibrium microstructure and resulting materials properties and performance. Thermodynamic, kinetic, and solidification models are used, including commercial software packages Thermo-Calc, Pandat™, and JMatPro®, and TC-PRISMA. Predicted powder properties can be used as input into a cold spray process impact model to determine the consolidated materials’ properties. Mechanical properties of powder particles are predicted as a function of powder particle diameter and are compared to experimental results.

Steepest-entropy-ascent quantum thermodynamics (SEAQT) is a mathematical and theoretical framework for intrinsic quantum thermodynamics (IQT), a unified theory of quantum mechanics and thermodynamics. In the theoretical framework, entropy is viewed as a measure of energy load sharing among available energy eigenlevels, and a unique relaxation path of a system from an initial non-equilibrium state to a stable equilibrium is determined from the greatest entropy generation viewpoint. The SEAQT modeling has seen a great development recently. However, the applications have mainly focused on gas phases, where a simple energy eigenstructure (a set of energy eigenlevels) can be constructed from appropriate quantum models by assuming that gas-particles behave independently. The focus of this research is to extend the applicability to solid phases, where interactions between constituent particles play a definitive role in their properties so that an energy eigenstructure becomes quite complicated and intractable from quantum models. To cope with the problem, a highly simplified energy eigenstructure (so-called ``pseudo-eigenstructure") of a condensed matter is constructed using a reduced-order method, where quantum models are replaced by typical solid-state models. The details of the approach are given and the method is applied to make kinetic predictions in various solid-state phenomena: the thermal expansion of silver, the magnetization of iron, and the continuous/discontinuous phase separation and ordering in binary alloys where a pseudo-eigenstructure is constructed using atomic/spin coupled oscillators or a mean-field approximation. In each application, the reliability of the approach is confirmed and the time-evolution processes are tracked from different initial states under varying conditions (including interactions with a heat reservoir and external magnetic field) using the SEAQT equation of motion derived for each specific application. Specifically, the SEAQT framework with a pseudo-eigenstructure successfully predicts: (i) lattice relaxations in any temperature range while accounting explicitly for anharmonic effects, (ii) low-temperature spin relaxations with fundamental descriptions of non-equilibrium temperature and magnetic field strength, and (iii) continuous and discontinuous mechanisms as well as concurrent ordering and phase separation mechanisms during the decomposition of solid-solutions.
Ph. D.
Many engineering materials have physical and chemical properties that change with time. The tendency of materials to change is quantified by the field of thermodynamics. The first and second laws of thermodynamics establish conditions under which a material has no tendency to change; these conditions are called equilibrium states. When a material is not in an equilibrium state, it is able to change spontaneously. Classical thermodynamics reliably identifies whether a material is susceptible to change, but it is incapable of predicting how change will take place or how fast it will occur. These are kinetic questions that fall outside the purview of thermodynamics. A relatively new theoretical treatment developed by Hatsopoulos, Gyftopoulos, Beretta and others over the past forty years extends classical thermodynamics into the kinetic realm. This framework, called steepest-entropy-ascent quantum thermodynamics (SEAQT), combines the tools of thermodynamics with quantum mechanics through a postulated equation of motion. Solving the equation of motion provides a kinetic description of the path a material will take as it changes from a non-equilibrium state to stable equilibrium. To date, the SEAQT framework has been applied primarily to systems of gases. In this dissertation, solid-state models are employed to extend the SEAQT approach to solid materials. The SEAQT framework is used to predict the thermal expansion of silver, the magnetization of iron, and the kinetics of atomic clustering and ordering in binary solid-solutions as a function of time or temperature. The model makes it possible to predict a unique kinetic path from any arbitrary, non-equilibrium, initial state to a stable equilibrium state. In each application, the approach is tested against experimental data. In addition to reproducing the qualitative kinetic trends in the cases considered, the SEAQT framework shows promise for modeling the behavior of materials far from equilibrium.

Knowledge of free-energy differences for states of a system provides an essential component in understanding many processes, including solubility, reaction rates, and phase changes. Therefore, the development of efficient, accurate free-energy calculation routines has long been of interest within the field of molecular modelling. Until recently, thermodynamic integration, free-energy perturbation and slow-change techniques were the only approaches available for the calculation of free-energy differences between two states of a system. However, with the discovery of non-equilibrium free-energy relations in the late nineties, new calculation approaches are now possible. This thesis demonstrates the application of these new relations by deriving them from statistical mechanical concepts and applying them to a variety of systems. Although other types of systems are considered, the focus of this work is on the investigation of density changes, as the density of a system is one of its fundamental intrinsic properties, and expansion and compression phenomena are central to many thermodynamic investigations. To investigate the convergence properties of the free-energy calculation methods prior to their application to systems undergoing a density change, a novel transformation between Lennard-Jones systems possessing different potentials is developed and simulations are completed for a variety of transformation parameters. In particular, the accuracy of free-energy calculations as a function of transformation rate is considered, along with a detailed analysis of free-energy convergence as a function of the number of transformations completed.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Biomolecular and Physical Sciences
Science, Environment, Engineering and Technology
Full Text

Dans ce travail, afin d'étudier la formation à l’équilibre et hors équilibre des hydrates mixtes de gaz, deux procédures de formation, rapide et lente, ont été appliqué à des mélanges de CH4-C2H6-C3H8-nC4H10-CO2-N2. L'objectif de ces deux procédures est d'examiner les effets cinétiques de la vitesse de cristallisation sur l'état final, soit dans des conditions dynamiques habituelles (formation rapide) soit en régime permanent (formation lente). Contrairement à la plupart des données de la littérature, qui fournissent uniquement des données de température-pression-composition gaz (PTy), cette étude fournit également la composition, le volume, la capacité de stockage, la densité de la phase hydrate, ou encore le nombre d'hydratation et la conversion d'eau. Les résultats montrent que, lors d'une cristallisation rapide, le volume d'hydrate augmente de 2% à 69% selon le mélange gazeux. De plus, la capacité de stockage diminue avec l'augmentation de la vitesse de cristallisation. En outre, un modèle thermodynamique, basé sur la méthode classique de van der Waals et Platteuw avec le potentiel de Kihara, a été utilisé. Un nouvel ensemble de paramètres Kihara pour le propane, basé sur une cristallisation lente, a été obtenu avec succès et comparé à la littérature. Les données sur la phase hydrates étant rares dans la littérature, ces dernières ont été collectées, et comparé au modèle thermodynamique précédent. Cela permet de mettre en évidence la capacité de la simulation à prédire la composition de la phase hydrate. Bien que ces outils soient intéressants pour prédire les équilibres de phase des molécules légères, ils deviennent moins fiables lorsque des transitions de phase se produisent (coexistence de structures) ou lorsque des molécules plus lourdes sont impliquées. Une analyse par spectroscopie RAMAN a d’ailleurs mis en évidence la coexistence de structures I et II pour un gaz riche en CO2 à partir d’un mélange CO2/C3H8. Pour conclure, la vitesse de cristallisation influence significativement le procédé de formation d’un hydrate mixte. L’utilisation d’un flash thermodynamique, combinant thermodynamique et bilan de masse, montre bien qu’une cristallisation lente est nécessaire pour satisfaire l’équilibre thermodynamique, et donc augmenter la capacité de stockage, et optimiser les procédés hydrate
In this work, in order to investigate the non-equilibrium behaviors of mixed clathrate hydrates, vapor-liquid-hydrate phase equilibria of mixed gas hydrates from CH4-C2H6-C3H8-nC4H10-CO2-N2 are studied. Two different experimental procedures are used: at quick and slow crystallization rates. The aim is to examine the effects of crystallization rate on the final state, either under usual dynamic (quick formation) or steady state conditions (slow formation). Unlike most of the literature data, providing temperature-pressure-vapor composition (PTy) results, this study also furnishes hydrate composition, volume, storage capacity, density, or hydration number and water conversion. At quick crystallization, hydrate volume increases from 2% to 69% according to the gas mixture. Moreover, storage capacity decreases with increasing rate of crystallization. In addition, a thermodynamic model, based on classical van der Waals and Platteuw method and Kihara potential, has been used. A new set of Kihara parameters for propane, based on slow crystallization, has been obtained successfully and compared to the literature.Besides, a review on guest composition in hydrates from experimental results is suggested, based on open literature. Then, the capability of thermodynamic modeling to simulate these rare data has been investigated. While simulation tools are interesting to predict phase equilibria for light molecules, they become less reliable when phase transition occurs in the system, or when heavier molecules are involved. In addition, the use of RAMAN spectroscopy has illustrated phase transition for CO2/C3H8 mixed hydrates under CO2 rich gas conditions.To conclude, the rate of crystallization significantly influences the process of mixed hydrates formation. The use of a thermodynamic flash shows that slow crystallization is necessary to satisfy the thermodynamic equilibrium, and thus increase storage capacity, and optimize hydrate processes

Application du logiciel aspen plus du mit au calcul des equilibres entre phases des systemes eau-hydrocarbures, et a l'optimisation d'une operation de lavage (exemple sur le charbon). On traite aussi de nouveaux calculs pour l'analyse de la stabilite thermodynamique de systemes complexes

L’activité scientifique du sujet porte sur l’acquisition de données expérimentales et la modélisation de la composition des clathrates hydrates de gaz. Les domaines d’application concernent la séparation et le stockage de gaz, la purification de l’eau, et le stockage d’énergie par matériaux à changement de phase.L’équipe a mis en évidence il y a quelques années que la composition des hydrates de gaz était sensible aux conditions de cristallisation, et que le phénomène de formation se produisait en dehors de l’équilibre thermodynamique.Le travail de thèse a permis d’explorer plusieurs modes de cristallisation à partir de solutions de même composition initiale pour observer les différences concernant l’état final, compositions notamment, et les relier à la vitesse de cristallisation. Suivant le mode de cristallisation, lent ou rapide, l’acquisition des données expérimentales peut prendre de quelques jours à plusieurs semaines. Les expériences sont réalisées en réacteur pressurisé dans lequel nous mesurons en ligne la composition de la phase gaz et de la phase liquide, pour calculer par bilan de matière la composition de la phase hydrate.Nous avons bien mis en évidence des variations dans la composition de la phase hydrate suivant le mode de cristallisation. Nous avons dû établir un modèle thermodynamique donnant la composition de la phase hydrate à l’équilibre pour des mélanges de gaz qui n’avaient jamais été traité par la littérature, et qui ont donc nécessité des campagnes de mesure extrêmement lentes et donc longues pour être sûr de l’état thermodynamique à l’équilibre.Nous sommes en cours d’établir un modèle cinétique pour modéliser les écarts à cet état d’équilibre de référence pour nos expériences réalisées à vitesse de cristallisation rapide
The scientific goal of this thesis is based on the acquisition of experimental data and the modeling of the composition of clathrates gas hydrate. The domains of application concern the gas separation and storage, water purification, and energy storage using change phase materials (PCMs).Our research team has recently demonstrated that the composition of gas hydrates was sensitive to the crystallization conditions, and that the phenomenon of formation was out of thermodynamic equilibrium. During this thesis, we have investigated several types of crystallization, which are based on the same initial states. The goal is to point out the differences between the initial solution composition and the final solution composition, and to establish a link between the final state and the crystallization rate.Depending on the rate of crystallization (slow or fast), the acquisition time of experimental data lasted from a few days to several weeks. The experimental tests were performed inside a stirred batch reactor (autoclave, 2.44 or 2.36 L) cooled with a double jacket. Real-time measurements of the composition of the gas and the liquid phases have been performed, in order to calculate the composition of the hydrate phase using mass balance calculations. Depending on the crystallization mode, we have identified several variations of the composition of the hydrate phase and final hydrate volume.We have established a successful thermodynamic model, which indicates the composition of the hydrate phase and hydrate volume in thermodynamic equilibrium state using a gas mixture which had never been used before in the literature. So this thermodynamic model has required an extremely slow experimental test. These tests were also long in order to be sure of the thermodynamic equilibrium state.We are currently establishing a kinetics model in order to model the deviations from the reference point of equilibrium of our experimental tests which were carried out at a high crystallization rate

Das Phasendiagramm Sn - Mo - O wurde für 500°C und 1000°C experimentell abgeleitet. Als ternäre Phasen konnten SnMo2O8 und Sn1-xMo4-yO6-2y dargestellt werden. Die Phasen SnMo5O8 und Sn4,4Mo24O38 konnten unterhalb von 1000°C nicht dargestellt werden. Die Phase SnMo2O8 wurde über Festkörper - Gasphasenreaktion einkristallin dargestellt und auf ihr thermisches Verhalten untersucht. Anhand dieser Untersuchungen konnte das Phasendiagramm SnO2 - MoO3 abgeleitet werden. An dieser Phase wurden Einkristall-untersuchungen durchgeführt. Die Struktur der Phase SnMo2O8 wurde in der Raumgruppe Pa (a = 8,967 Å) gelöst. Die Zinnatome besetzen die Flächen - und Kantenmitten der Elementarzelle. Die Lage der Molybdän - und Sauerstoffpositionen kann über ein Fehlordnungsmodell beschrieben werden. Die Phase Sn1-xMo4-yO6-2y konnte über chemischen Transport mit Wasser einkristallin hergestellt werden. Einkristalluntersuchungen bestätigten eine Überstruktur zur NaMo4O6 - Struktur. Die Phase weist mit hoher Wahrscheinlichkeit eine Unterstöchiometrie im Zinngehalt, sowie im Molybdän - bzw. Sauerstoffgehalt auf. Diese Tatsache konnte durch Mößbaueruntersuchungen am Pulver von Sn1-xMo4-yO6-2y bestätigt werden. Eine Lösung der Struktur von Sn1-xMo4-yO6-2y war bisher nicht möglich. Die thermodynamischen Daten der Phasen SnMo2O8 und SnMo4O6 (vereinfacht für Sn1-xMo4-yO6-2y) konnten theoretisch abgeleitet werden. Das Zustandsdiagramm Sn - Mo - O wurde berechnet. Die Überprüfung der Daten erfolgte durch die Berechnung der Bodenkörper - Gasphasengleichgewichte mit dem Programm TRAGMIN. Mit den abgeleiteten Daten wurden Berechnungen zum chemischen Transportverhalten durchgeführt. Dabei wurde gefunden, dass sich die Phase Sn1-xMo4-yO6-2y über chemischen Transport abscheiden lässt. Das Phasendiagramm Pb - Mo - O wurde bis 1000°C experimentell abgeleitet. Die Phasen PbMoO4 und Pb2MoO5 konnten als einphasige Pulver hergestellt werden. Die Phase Pb0,75Mo4O6 konnte über chemischen Transport einkristallin abgeschieden werden. Beim Erhitzen auf 1250°C wurde die Zersetzung dieser Phase in die Phase PbMo5O8 und Mo beobachtet. Die thermodynamischen Daten der Phasen PbMoO4, Pb2MoO5, Pb5MoO8 und Pb0,75Mo4O6 konnten theoretisch abgeleitet werden. Das Zustandsdiagramm Pb - Mo - O wurde berechnet. Im Verlauf der Rechnungen wurde das Zustandsdiagramm PbO - MoO3 mit dem Programm CHEMSAGE berechnet und mit den Literaturdaten verglichen. Die Überprüfung der Daten erfolgte durch die Berechnung der Bodenkörper - Gasphasengleichgewichte mit dem Programm TRAGMIN. Mit den abgeleiteten Daten wurden Berechnungen zum chemischen Transportverhalten durchgeführt. Dabei wurde gefunden, dass sich die Phase Pb0,75Mo4O6 über chemischen Transport abscheiden lässt. Das Phasendiagramm Sb - Mo - O wurde bei 500°C bzw. 700°C experimentell abgeleitet. Im System existieren die Phasen Sb2MoO6 und Sb2Mo10O31. Sb2Mo10O31 konnte einphasig als Pulver hergestellt werden. Die Existenz einer Phase mit der Zusammensetzung Sb4Mo10O31 konnte nicht bestätigt werden. Es wurden Hinweise auf eine dritte ternäre Phase im System Sb - Mo - O gefunden. Die Phasen Sb2MoO6 und Sb2Mo10O31 konnten über chemischen Transport einkristallin dargestellt werden. Mößbaueruntersuchungen an Sb2Mo10O31 ergaben, dass in der Verbindung ausschliesslich dreiwertiges Sb vorliegt und somit Mo gemischtvalent sein muss. Die thermodynamischen Daten der Phasen Sb2MoO6 und Sb2Mo10O31 konnten theoretisch abgeleitet werden. Das Zustandsdiagramm Sb - Mo - O wurde berechnet. Die Überprüfung der Daten erfolgte durch die Berechnung der Bodenkörper - Gasphasengleichgewichte mit dem Programm TRAGMIN. Mit den abgeleiteten Daten wurden Berechnungen zum chemischen Transportverhalten durchgeführt. Dabei wurde gefunden, dass sich beide ternäre Phasen über chemischen Transport abscheiden lassen.

Les calculs d'équilibres à triphasiques et quadriphasiques sont au cœur des simulations de réservoirs impliquant des processus de récupérations tertiaires. Dans les procédés d'injection de gaz ou de vapeur, le système huile-gaz est enrichi d'une nouvelle phase qui joue un rôle important dans la récupération de l'huile en place. Les calculs d'équilibres représentent la majeure partie des temps de calculs dans les simulations de réservoir compositionnelles où les routines thermodynamiques sont appelées un nombre conséquent de fois. Il est donc important de concevoir des algorithmes qui soient fiables, robustes et rapides. Dans la littérature peu de simulateurs basés sur des équations d'état sont applicables aux procédés de récupération thermique. A notre connaissance, il n'existe pas de simulation thermique complètement compositionnelle de ces procédés pour des cas d'applications aux huiles lourdes. Ces simulations apparaissent essentielles et pourraient offrir des outils améliorés pour l’étude prédictive de certains champs. Dans cette thèse, des algorithmes robustes et efficaces de calculs d’équilibre multiphasiques sont proposés permettant de surmonter les difficultés rencontrés durant les simulations d'injection de vapeur pour des huiles lourdes. La plupart des algorithmes d'équilibre de phases sont basés sur la méthode de Newton et utilisent les variables conventionnelles comme variables indépendantes. Dans un premier temps, des améliorations de ces algorithmes sont proposées. Les variables réduites permettent de réduire la dimensionnalité du système de nc (nombre de composants) dans le cas des variables conventionnelles, à M (M<
Three to four phase equilibrium calculations are in the heart of tertiary recovery simulations. In gas/steam injection processes, additional phases emerging from the oil-gas system are added to the set and have a significant impact on the oil recovery. The most important computational effort in many chemical process simulators and in petroleum compositional reservoir simulations is required by phase equilibrium and thermodynamic property calculations. In field scale reservoir simulations, a huge number of phase equilibrium calculations is required. For all these reasons, the algorithms must be robust and time-saving. In the literature, few simulators based on equations of state (EoS) are applicable to thermal recovery processes such as steam injection. To the best of our knowledge, no fully compositional thermal simulation of the steam injection process has been proposed with extra-heavy oils; these simulations are essential and will offer improved tools for predictive studies of the heavy oil fields. Thus, in this thesis different algorithms of improved efficiency and robustness for multiphase equilibrium calculations are proposed, able to handle conditions encountered during the simulation of steam injection for heavy oil mixtures. Most of the phase equilibrium calculations are based on the Newton method and use conventional independent variables. These algorithms are first investigated and different improvements are proposed. Michelsen’s (Fluid Phase Equil. 9 (1982) 21-40) method for multiphase-split problems is modified to take full advantage of symmetry (in the construction of the Jacobian matrix and the resolution of the linear system). The reduction methods enable to reduce the space of study from nc (number of components) for conventional variables to M (M<

Phase behaviour information is essential for the development and optimization of hydrocarbon resource production, transport and refining technologies. Experimental data sets for mixtures containing heavy oil and bitumen are sparse as phase behaviour data are difficult to obtain and cost remains prohibitive for most applications. A computational tool that predicts phase behaviours reliably for mixtures containing such ill-defined components, over broad temperature, pressure and composition ranges would play a central role in the advancement of bitumen production and refining process knowledge and would have favourable impacts on the economics and environmental effects linked to the exploitation of such ill-defined hydrocarbon resources. Prior to this work, predictive computational methods were reliable for dilute mixtures of ill-defined constituents. To include a much wider range of conditions, three major challenges were addressed. The challenges include: creation of a robust and accurate numerical approach, implementation of a reliable thermodynamic model, and speciation of ill-defined constituents like Athabasca Bitumen Vacuum Residue (AVR). The first challenge was addressed by creating a novel computational approach based on a global minimization method for phase equilibrium calculations. The second challenge was tackled by proposing a thermodynamic model that combines the Peng-Robinson equation of state with group contribution and related parameter prediction methods. The speciation challenge was addressed by another research group at the University of Alberta. Pseudo components they proposed were used to assign groups and estimate thermodynamic properties. The new phase equilibrium computational tool was validated by comparing simulated phase diagrams with experimental data for mixtures containing AVR and n-alkanes. There is good qualitative and quantitative agreement between computed and experimental phase diagrams over industrially relevant ranges of compositions, pressures and temperatures. Mismatch was only observed over a limited range of compositions, temperatures and pressures. This computational breakthrough provides, for the first time, a platform for reliable phase behaviour computations with broad potential for application in the hydrocarbon resource sector. The specific computational results can be applied directly to solvent assisted recovery, paraffinic deasphalting, and distillation and refining processes for Athabasca bitumen a strategic resource for Canada.
Chemical Engineering

Dissertação de Mestrado Integrado em Engenharia Mecânica apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra
The production of ceramics nanoparticles by detonation of metalized emulsions is an important alternative to the traditional metallurgic methods. The small size of the obtained particles (high pressure reaction), the reliability of reaction process (detonation), high temperature post-detonation particles formation with extremely fast cooling (due to the speed of adiabatic expansion of the gases), and the control of product condensed phase composition are the main advantages. This innovative emulsion detonation synthesis method (EDSM), can be included in either solid or gas-phase synthesis manufacturing process depending on the chosen conditions, and emerges as the most promising technique for the industrialization of the nanoparticles production. In this work, this production method is studied for metal oxide formation. These materials are chosen given its excellent properties, due to the combination of covalent and ionic links with strong chemical bonds, such as: high hardness and mechanical resistance at high temperature, high melting temperatures which allows good thermal and electric insulating applications and the exhibition of high chemical stability in hostile environment. These properties make these ceramic materials appropriate for several industrial applications. Metal oxide production from detonation can be predicted using Thermochemical Codes, in this case with THOR Code. For the modelling of this particles formation, the temperature of detonation is the most important parameter to know, as well as the products concentration, being these variables the focus of the modeling problem. Given this problem, the implementation of a thermal equation of state and energetic equation of state is essential in order to better define solid products. Therefore, it’s necessary to derive this equations for each phase of solid condensed species. In this work a Cowan & Fickett Thermal Equations of State and a Mie-Grüneisen approach with thermal contribution given by Debye model Energetic Equation of State are used to describe these solids. These equations are different and characterize more accurately the behavior of metal oxide particles (solid condensed phase) formation in Thor than the ones previously used (which represented metal oxide particles as a high density gas (Gordon McBride Polynomials)). The parameters used in this models are known only for common and wellstudied products, so the objective of this work was finding these parameters for Alumina, Zirconia, Titania and Magnesia, and simulate each one of this material formation. Before the metal oxide condensed specie formation analysis, a benchmark was made with Carbon condensed species formation, given its common and abundant presence in reactive mixtures formed in shock compressed energetic materials. The results comparison proved the validity of the models and methods used in the derivation of the parameters and the possibility of extrapolate them for other simulations. Multiple papers were studied and reviewed in order to derive this parameters for each material at a given phase. These equations were applied in Thor Database, which allowed the simulation of their formation and comparison with the previous method, proving the better accuracy in obtaining the Temperature and Pressure of Detonation, as well as the product concentration.
A produção de nanopartículas cerâmicas por detonação de emulsões metalizadas é uma alternativa importante aos métodos metalúrgicos tradicionais. O tamanho reduzido das partículas obtidas (reação a alta pressão), a fiabilidade do processo da reação (detonação), a formação de partículas em altas temperaturas na pós-detonação com arrefecimento rápido (devido à elevada velocidade de expansão adiabática dos gases) e o controlo da composição da fase condensada são as principais vantagens deste método. Este processo de fabricação inovador, Emulsion Detonation Synthesis Method (EDSM), pode ser definido como um processo de síntese em fase sólida ou gasosa, de acordo com as condições escolhidas, e destaca-se como uma técnica promissora na industrialização da produção de nanopartículas. Neste trabalho é analisada a produção de nanopartículas de Óxidos Metálicos por detonação. Estes materiais são escolhidos devido às suas excelentes propriedades, devido à coexistência de ligações iónicas e covalentes com fortes ligações, tais como: elevada dureza e resistência mecânica a temperaturas elevadas, altas temperaturas de fusão que permitem a sua introdução em aplicações de isolamento térmico e elétrico e ainda a elevada estabilidade química em ambiente adverso. Estas propriedades fazem destes materiais cerâmicos apropriados para diversas aplicações industriais. A produção de óxidos metálicos por detonação pode ser modelada através de programas termoquímicos, neste caso através do programa termoquímico THOR. Para a modelação da formação destas partículas, a temperatura de detonação é a variável mais importante de obter, tal como a concentração dos produtos, sendo considerados o principal objetivo de modelação. Por esta razão, a implementação de equações de estado (térmicas e energéticas) é essêncial, de modo a melhor definir os produtos sólidos. Assim, é necessário derivar estas equações para cada fase de material condensado nos produtos da detonação. Neste trabalho, são utilizadas as Equações Cowan & Fickett para a definição do estado térmico e uma abordagem Mie-Grüneisen com a contribuição térmica dada pelo modelo de Debye para a equação de estado energética, de modo a descrever os sólidos definidos. Estas equações caracterizam mais fielmente o comportamento da formação de partículas de óxidos metálicos (fase sólida condensada) no THOR do que as equações usadas previamente (que representavam as partículas como um gás de elevada densidade (Gordon McBride Polynomials)). Os parâmetros usados nestes modelos são conhecidos apenas para produtos extensamente estudados. Por este motivo, este trabalho centra-se na determinação destes parâmetros para a Alumina, Zircónica, Titania e Magnésia, simulando posteriormente a formação de cada um destes materiais através das equações definidas. Antes da análise da formação de óxidos metálicos na detonação foi realizado um estudo de referência através da formação de espécies condensadas de Carbono, dado o seu extenso estudo e a sua presença nos produtos de misturas reativas de materiais energéticos. A comparação destes resultados provou a validade dos modelos e métodos utilizados na derivação dos parâmetros, bem como a possibilidade de extrapolação para outras simulações. Foram analisados vários artigos com o objetivo de derivar os parâmetros referidos para cada material numa dada fase. Estas equações foram implementadas na base de dados do THOR, o que permitiu a simulação da sua formação e a comparação com os métodos anteriormente usados, provando uma melhor precisão na obtenção das temperaturas e pressões de detonação, bem como na previsão de concentração dos produtos.