Modelling of advection-dominated transport in fluid-saturated porous media

The modelling of contaminant transport in porous media is an important topic to geosciences and geo-environmental engineering. An accurate assessment of the spatial and temporal distribution of a contaminant is an important step in the environmental decision-making process. Contaminant transport in porous media usually involves complex non-linear processes that result from the interaction of the migrating chemical species with the geological medium. The study of practical problems in contaminant transport therefore usually requires the development of computational procedures that can accurately examine the non-linear coupling processes involved. However, the computational modelling of the advection-dominated transport process is particularly sensitive to situations where the concentration profiles can exhibit high gradients and/or discontinuities. This thesis focuses on the development of an accurate computational methodology that can examine the contaminant transport problem in porous media where the advective process dominates.The development of the computational method for the advection-dominated transport problem is based on a Fourier analysis on stabilized semi-discrete Eulerian finite element methods for the advection equation. The Fourier analysis shows that under the Courant number condition of Cr=1, certain stabilized finite element scheme can give an oscillation-free and non-diffusive solution for the advection equation. Based on this observation, a time-adaptive scheme is developed for the accurate solution of the one-dimensional advection-dominated transport problem with the transient flow velocity. The time-adaptive scheme is validated with an experimental modelling of the advection-dominated transport problem involving the migration of a chemical solution in a porous column. A colour visualization-based image processing method is developed in the experimental modelling to quantitatively determinate the chemical concentration on the porous column in a non-invasive way. A mesh-refining adaptive scheme is developed for the optimal solution of the multi-dimensional advective transport problem with a time- and space-dependent flow field. Such mesh-refining adaptive procedure is quantitative in the sense that the size of the refined mesh is determined by the Courant number criterion. Finally, the thesis also presents a brief study of a numerical model that is capable to capture coupling Hydro-Mechanical-Chemical processes during the advection-dominated transport of a contaminant in a porous medium

A time-dependent green element formulation for solution of potential flow problems in 3 dimensional domains

In this work we develop a generalised methodology for the solution of the timedependent second order parabolic differential equation of potential flow in heterogeneous media using the Green element method. Parabolic differential equations are one class of differential equations, the others being elliptic partial differential equations and hyperbolic differential equations. Since elliptic differential equations generally arise from a diffusion process that has reached equilibrium, they can also be solved using the methodology developed, and represent a simplification because of the steady state situation. Potential flow problems are of great interest in many engineering applications such as flow in aquifers, heat transfer processes, electro-magnetic field problems, etc. Traditionally, the finite difference method and the finite element method have proved to be powerful techniques to solve such potential flow problems, but each has limitations and challenges which have led to continued research in numerical methods. The finite difference method is more applicable to domains with regular boundary, and the finite element method, though extremely versatile, exhibits unacceptable inaccuracies with coarse meshes, thus requiring fine meshes with the associated high computation costs. In view of some of the limitations with these earlier methods, several numerical schemes are now being developed as viable alternatives to these conventional methods. Among such methods are the boundary element method, the finite volume method, and the analytic element method. The boundary element method has been particularly promising because of its domain-reduction feature and the second order accuracy that can generally be achieved. The domain-reduction feature of the boundary element method, though achieved for restricted class of problems, lends it to efficient grid generation algorithm, while its second-order accuracy ensures reliability and consistency of the numerical solutions. -v- The boundary element method in its original formulation is unable to deal with heterogeneities in the domain. For physical problems, especially in groundwater flow, heterogeneities and anisotropy are a natural and frequent occurrence, and this has fuelled research into boundary element techniques that are capable of accommodating these features. The Green element method is one technique which is based on the boundary element theory and which has been proven to be very effective in handling heterogeneities and anisotropy in 1D and 2D domains. However, development of techniques to implement the Green element method in 3D domains has remained largely unexplored. This work represents an effort in this direction. We have investigated the adoption of the general tetrahedral and hexahedra elements for use with the Green element method, and found that the large number of degrees of freedom generated precludes retention of the internal normal direction as in 1D and 2D formulations. Furthermore, some of the complicated surface and domain integrations with these elements can only be addressed with quadrature methods. The compatibility issues that arise between element faces, which present considerable challenges to multi-domain boundary element techniques, are innovatively addressed in the computer code that has been developed in this work. The Green element method is implemented for steady and time-dependent problems using regular hexahedra elements, and the results show that the performance is slightly better than the results obtained using FEMWATER. FEMWATER is an established finite element method software. No attempt is made to compare the computation efficiencies of the 3D GEM code and FEMWATER because the two codes were not developed on a common platform

Análise Biomecânica de Calo Ósseo usando Método Sem Malha

O osso é um tecido fisiologicamente dinâmico e que quando lesionado tem a capacidade de se reparar com o próprio tecido, não envolvendo um tecido cicatrizante, ao contrário de outros tecidos. Esta característica torna-o particularmente interessante para investigar os processos inerentes de fraturas ósseas. A maior parte das fraturas cicatriza através de uma sequência de processos de diferenciação de tecidos, desde os processos iniciais de hematoma, aos tecidos conjuntivos, e através da cartilagem ao osso. No entanto, qualquer falha neste processo pode resultar em uniões tardias, más uniões ou não uniões. A compreensão na totalidade deste processo ainda constitui um desafio. Os mecanismos que envolvem os processos de estimulação mecânica não se encontram bem compreendidos, em consequência da complexidade dos testes experimentais in vivo, que se tornam dependentes de dados in vitro, tornando difícil validar os pressupostos biológicos. Consequentemente, os modelos computacionais têm demonstrado serem bastante úteis e eficazes na investigação sobre a cicatrização óssea. Desta forma, com o presente trabalho foi possível analisar as condições mecânicas de um calo ósseo resultante de uma fratura, assim como compreender as metodologias de análise numérica aplicadas. O modelo teve por base um estudo in vivo de forma a obter uma variação temporal progressiva da forma do calo e das propriedades mecânicas durante a cicatrização óssea. Com este modelo obtiveram-se os campos de tensão e deformação nas diferentes fases do processo de regeneração, obtendo-se resultados que se encontram em conformidade com a literatura. Adicionalmente, foi aplicado um algoritmo de remodelação óssea em combinação com o Radial Point Interpolation Method (RPIM) que foi capaz de reproduzir as condições apresentadas pela respetiva imagem histológica nesta fase. Por último, espera-se que os trabalhos desenvolvidos neste âmbito possibilitem a conceção de estratégias mais precisas e eficazes tanto para o tratamento como para aceleração da cura. De forma complementar, encontram-se em desenvolvimento modelos específicos dos pacientes e que incorporam variabilidade genética.Bone is a physiologically dynamic tissue that, when injured, has the ability to repair itself, not involving scar tissue, unlike other tissues. This characteristic makes it particularly interesting for investigating the inherent processes of bone fractures. Most fractures heal through a sequence of tissue differentiation processes, from the initial hematoma, to connective tissues and through cartilage to bone. However, any failure in this process can result in a delayed union, mal-union or non-union. A complete understanding of this process is still a challenge. The mechanisms surrounding the mechanical stimulation processes are relatively poorly understood as a result of the complexity of in vivo experimental tests, which become dependent on in vitro data, making it difficult to validate the biological assumptions. Consequently, computational models have proven to be very useful and effective in the investigation of bone healing. Therefore, in the present work, it was possible to analyse the mechanical conditions of a bone callus as a consequence of a fracture and to understand the methodologies of numerical analysis applied. The model was based on an in vivo experimental study in order to obtain a progressive temporal variation of the callus shape and mechanical properties during bone healing. With this model, the stress and strain fields in the different phases of the regeneration process were obtained, where the results are in agreement with the literature. Additionally, a bone remodelling algorithm was applied in combination with the Radial Point Interpolation Method (RPIM), which was able to reproduce the conditions presented by the respective histological image at this stage. Finally, it is expected that the work developed in this area will enable the design of more accurate and effective strategies for both treatment and accelerating healing. Complementarily, patient-specific models and the incorporation of genetic variability are being developed

Numerical simulation of unsaturated flow using modified transformation methods

Ph.DDOCTOR OF PHILOSOPH

Efficient simulation tools for real-time monitoring and control using model order reduction and data-driven techniques

Numerical simulation, the use of computers to run a program which implements a mathematical model for a physical system, is an important part of today technological world. It is required in many scientific and engineering fields to study the behaviour of systems whose mathematical models are too complex to provide analytical solutions and it makes virtual evaluation of systems responses possible (virtual twins). This drastically reduces the number of experimental tests for accurate designs of the real system that the numerical model represents. However these virtual twins, based on classical methods which make use of a rich representations of the system (ex. finite element method), rarely allows real-time feedback, even when considering high performance computing, operating on powerful platforms. In these circumstances, the real-time performance required in some applications are compromised. Indeed the virtual twins are static, that is, they are used in the design of complex systems and their components, but they are not expected to accommodate or assimilate data so as to define dynamic data-driven application systems. Moreover significant deviations between the observed response and the one predicted by the model are usually noticed due to inaccuracy in the employed models, in the determination of the model parameters or in their time evolution. In this thesis we propose different methods to solve these handicaps in order to perform real-time monitoring and control. In the first part Model Order Reduction (MOR) techniques are used to accommodate real-time constraints; they compute a good approximation of the solution by simplifying the solution procedure instead of the model. The accuracy of the predicted solution is not compromised and efficient simulations can be performed (digital twins). In the second part Data-Driven modelling are employed to fill the gap between the parametric solution computed by using non-intrusive MOR techniques and the measured fields, in order to make dynamic data-driven application systems, DDDAS, possible (Hybrid Twins).La simulación numérica, el uso de ordenadores para ejecutar un programa que implementa un modelo matemático de un sistema físico, es una parte importante del mundo tecnológico actual. En muchos campos de la ciencia y la ingeniería es necesario estudiar el comportamiento de sistemas cuyos modelos matemáticos son demasiado complejos para proporcionar soluciones analíticas, haciendo posible la evaluación virtual de las respuestas de los sistemas (gemelos virtuales). Esto reduce drásticamente el número de pruebas experimentales para los diseños precisos del sistema real que el modelo numérico representa. Sin embargo, estos gemelos virtuales, basados en métodos clásicos que hacen uso de una rica representación del sistema (por ejemplo, el método de elementos finitos), rara vez permiten la retroalimentación en tiempo real, incluso cuando se considera la computación en plataformas de alto rendimiento. En estas circunstancias, el rendimiento en tiempo real requerido en algunas aplicaciones se ve comprometido. En efecto, los gemelos virtuales son estáticos, es decir, se utilizan en el diseño de sistemas complejos y sus componentes, pero no se espera que acomoden o asimilen los datos para definir sistemas de aplicación dinámicos basados en datos. Además, se suelen apreciar desviaciones significativas entre la respuesta observada y la predicha por el modelo, debido a inexactitudes en los modelos empleados, en la determinación de los parámetros del modelo o en su evolución temporal. En esta tesis se proponen diferentes métodos para resolver estas limitaciones con el fin de realizar un seguimiento y un control en tiempo real. En la primera parte se utilizan técnicas de Reducción de Modelos para satisfacer las restricciones en tiempo real; estas técnicas calculan una buena aproximación de la solución simplificando el procedimiento de resolución en lugar del modelo. La precisión de la solución no se ve comprometida y se pueden realizar simulaciones efficientes (gemelos digitales). En la segunda parte se emplea la modelización basada en datos para llenar el vacío entre la solución paramétrica, calculada utilizando técnicas de reducción de modelos no intrusivas, y los campos medidos, con el fin de hacer posibles los sistemas de aplicación dinámicos basados en datos (gemelos híbridos).La simulation numérique, c'est-à-dire l'utilisation des ordinateurs pour exécuter un programme qui met en oeuvre un modèle mathématique d'un système physique, est une partie importante du monde technologique actuel. Elle est nécessaire dans de nombreux domaines scientifiques et techniques pour étudier le comportement de systèmes dont les modèles mathématiques sont trop complexes pour fournir des solutions analytiques et elle rend possible l'évaluation virtuelle des réponses des systèmes (jumeaux virtuels). Cela réduit considérablement le nombre de tests expérimentaux nécessaires à la conception précise du système réel que le modèle numérique représente. Cependant, ces jumeaux virtuels, basés sur des méthodes classiques qui utilisent une représentation fine du système (ex. méthode des éléments finis), permettent rarement une rétroaction en temps réel, même dans un contexte de calcul haute performance, fonctionnant sur des plates-formes puissantes. Dans ces circonstances, les performances en temps réel requises dans certaines applications sont compromises. En effet, les jumeaux virtuels sont statiques, c'est-à-dire qu'ils sont utilisés dans la conception de systèmes complexes et de leurs composants, mais on ne s'attend pas à ce qu'ils prennent en compte ou assimilent des données afin de définir des systèmes d'application dynamiques pilotés par les données. De plus, des écarts significatifs entre la réponse observée et celle prévue par le modèle sont généralement constatés en raison de l'imprécision des modèles employés, de la détermination des paramètres du modèle ou de leur évolution dans le temps. Dans cette thèse, nous proposons di érentes méthodes pour résoudre ces handicaps afin d'effectuer une surveillance et un contrôle en temps réel. Dans la première partie, les techniques de Réduction de Modèles sont utilisées pour tenir compte des contraintes en temps réel ; elles calculent une bonne approximation de la solution en simplifiant la procédure de résolution plutôt que le modèle. La précision de la solution n'est pas compromise et des simulations e caces peuvent être réalisées (jumeaux numériquex). Dans la deuxième partie, la modélisation pilotée par les données est utilisée pour combler l'écart entre la solution paramétrique calculée, en utilisant des techniques de réduction de modèles non intrusives, et les champs mesurés, afin de rendre possibles des systèmes d'application dynamiques basés sur les données (jumeaux hybrides)

Investigating capillary pressure and interfacial area for multiphase flow in porous media using pore-scale imaging and lattice-Boltzmann modeling

Recent advances in imaging technology and numerical modeling have greatly enhanced pore-scale investigations of multiphase flow and transport in porous media. It is now feasible to obtain high resolution 3-dimensional pore-scale data, and numerical methods such as the lattice- Boltzmann (LB) technique have been developed specifically for simulating such phenomena. Traditional macro-scale multiphase flow models rely heavily on empirical relationships. For example, the interaction between fluids at their interfaces is accounted for indirectly through the empirical relative permeability relationship. Nevertheless, it has recently been hypothesized that the single most important variable missing from current macro-scale models is the measure of interfacial dynamics between fluids within the pores. Furthermore, the empirical capillary pressure-saturation relationship used in macro-scale multiphase flow simulators has been shown to be a function of interfacial area per volume. This study focuses on (1) the measurement and modeling of the capillary pressure-saturation relationship; and (2) the characterization of the fluid-fluid interfacial area per volume as a function of saturation. The study synthesizes experimental results derived from pore-scale computerized micro-tomographic (CMT) images with LB simulations. An image analysis algorithm for quantifying fluid-fluid interfacial area per volume from experimental CMT and simulation images was developed and verified. The experimental results were shown to be in good agreement with values reported in the literature. Furthermore, the capillary ressure-saturation curves were used to validate a recently proposed macro-scale interfacial area model. New LB simulations of drainage and imbibition for an air-water system were developed, in which the full geometry from the experimental system was used to define the lattice. This allowed for the direct comparison of experimental and simulated phase distributions within the pores. LB simulations showed excellent agreement with experimental results, considering no optimization or calibration to the data was required. Collectively, results show that there is a complex functional relationship between capillary pressure, saturation and interfacial area that provides insights into multiphase flow and transport processes that can not be obtained from the capillary pressure-saturation relationship alone

Efficient simulation tools for real-time monitoring and control using model order reduction and data-driven techniques

Cotutela: Universitat Politècnica de Catalunya i École Centrale de Nantes.Numerical simulation, the use of computers to run a program which implements a mathematical model for a physical system, is an important part of today technological world. It is required in many scientific and engineering fields to study the behaviour of systems whose mathematical models are too complex to provide analytical solutions and it makes virtual evaluation of systems responses possible (virtual twins). This drastically reduces the number of experimental tests for accurate designs of the real system that the numerical model represents. However these virtual twins, based on classical methods which make use of a rich representations of the system (ex. finite element method), rarely allows real-time feedback, even when considering high performance computing, operating on powerful platforms. In these circumstances, the real-time performance required in some applications are compromised. Indeed the virtual twins are static, that is, they are used in the design of complex systems and their components, but they are not expected to accommodate or assimilate data so as to define dynamic data-driven application systems. Moreover significant deviations between the observed response and the one predicted by the model are usually noticed due to inaccuracy in the employed models, in the determination of the model parameters or in their time evolution. In this thesis we propose different methods to solve these handicaps in order to perform real-time monitoring and control. In the first part Model Order Reduction (MOR) techniques are used to accommodate real-time constraints; they compute a good approximation of the solution by simplifying the solution procedure instead of the model. The accuracy of the predicted solution is not compromised and efficient simulations can be performed (digital twins). In the second part Data-Driven modelling are employed to fill the gap between the parametric solution computed by using non-intrusive MOR techniques and the measured fields, in order to make dynamic data-driven application systems, DDDAS, possible (Hybrid Twins).La simulación numérica, el uso de ordenadores para ejecutar un programa que implementa un modelo matemático de un sistema físico, es una parte importante del mundo tecnológico actual. En muchos campos de la ciencia y la ingeniería es necesario estudiar el comportamiento de sistemas cuyos modelos matemáticos son demasiado complejos para proporcionar soluciones analíticas, haciendo posible la evaluación virtual de las respuestas de los sistemas (gemelos virtuales). Esto reduce drásticamente el número de pruebas experimentales para los diseños precisos del sistema real que el modelo numérico representa. Sin embargo, estos gemelos virtuales, basados en métodos clásicos que hacen uso de una rica representación del sistema (por ejemplo, el método de elementos finitos), rara vez permiten la retroalimentación en tiempo real, incluso cuando se considera la computación en plataformas de alto rendimiento. En estas circunstancias, el rendimiento en tiempo real requerido en algunas aplicaciones se ve comprometido. En efecto, los gemelos virtuales son estáticos, es decir, se utilizan en el diseño de sistemas complejos y sus componentes, pero no se espera que acomoden o asimilen los datos para definir sistemas de aplicación dinámicos basados en datos. Además, se suelen apreciar desviaciones significativas entre la respuesta observada y la predicha por el modelo, debido a inexactitudes en los modelos empleados, en la determinación de los parámetros del modelo o en su evolución temporal. En esta tesis se proponen diferentes métodos para resolver estas limitaciones con el fin de realizar un seguimiento y un control en tiempo real. En la primera parte se utilizan técnicas de Reducción de Modelos para satisfacer las restricciones en tiempo real; estas técnicas calculan una buena aproximación de la solución simplificando el procedimiento de resolución en lugar del modelo. La precisión de la solución no se ve comprometida y se pueden realizar simulaciones efficientes (gemelos digitales). En la segunda parte se emplea la modelización basada en datos para llenar el vacío entre la solución paramétrica, calculada utilizando técnicas de reducción de modelos no intrusivas, y los campos medidos, con el fin de hacer posibles los sistemas de aplicación dinámicos basados en datos (gemelos híbridos).La simulation numérique, c'est-à-dire l'utilisation des ordinateurs pour exécuter un programme qui met en oeuvre un modèle mathématique d'un système physique, est une partie importante du monde technologique actuel. Elle est nécessaire dans de nombreux domaines scientifiques et techniques pour étudier le comportement de systèmes dont les modèles mathématiques sont trop complexes pour fournir des solutions analytiques et elle rend possible l'évaluation virtuelle des réponses des systèmes (jumeaux virtuels). Cela réduit considérablement le nombre de tests expérimentaux nécessaires à la conception précise du système réel que le modèle numérique représente. Cependant, ces jumeaux virtuels, basés sur des méthodes classiques qui utilisent une représentation fine du système (ex. méthode des éléments finis), permettent rarement une rétroaction en temps réel, même dans un contexte de calcul haute performance, fonctionnant sur des plates-formes puissantes. Dans ces circonstances, les performances en temps réel requises dans certaines applications sont compromises. En effet, les jumeaux virtuels sont statiques, c'est-à-dire qu'ils sont utilisés dans la conception de systèmes complexes et de leurs composants, mais on ne s'attend pas à ce qu'ils prennent en compte ou assimilent des données afin de définir des systèmes d'application dynamiques pilotés par les données. De plus, des écarts significatifs entre la réponse observée et celle prévue par le modèle sont généralement constatés en raison de l'imprécision des modèles employés, de la détermination des paramètres du modèle ou de leur évolution dans le temps. Dans cette thèse, nous proposons di érentes méthodes pour résoudre ces handicaps afin d'effectuer une surveillance et un contrôle en temps réel. Dans la première partie, les techniques de Réduction de Modèles sont utilisées pour tenir compte des contraintes en temps réel ; elles calculent une bonne approximation de la solution en simplifiant la procédure de résolution plutôt que le modèle. La précision de la solution n'est pas compromise et des simulations e caces peuvent être réalisées (jumeaux numériquex). Dans la deuxième partie, la modélisation pilotée par les données est utilisée pour combler l'écart entre la solution paramétrique calculée, en utilisant des techniques de réduction de modèles non intrusives, et les champs mesurés, afin de rendre possibles des systèmes d'application dynamiques basés sur les données (jumeaux hybrides).Postprint (published version