Provenance does matter: Links between winter trophic segregation and the migratory origins of European robins

Amongst migratory species, it is common to find individuals from different populations or geographical origins sharing staging or wintering areas. Given their differing life histories, ecological theory would predict that the different groups of individuals should exhibit some level of niche segregation. This has rarely been investigated because of the difficulty in assigning migrating individuals to breeding areas. Here, we start by documenting a broad geographical gradient of hydrogen isotopes (δ (2)H) in robin Erithacus rubecula feathers across Europe. We then use δ (2)H, as well as wing-tip shape, as surrogates for broad migratory origin of birds wintering in Iberia, to investigate the ecological segregation of populations. Wintering robins of different sexes, ages and body sizes are known to segregate between habitats in Iberia. This has been attributed to the despotic exclusion of inferior competitors from the best patches by dominant individuals. We find no segregation between habitats in relation to δ (2)H in feathers, or to wing-tip shape, which suggests that no major asymmetries in competitive ability exist between migrant robins of different origins. Trophic level (inferred from nitrogen isotopes in blood) correlated both with δ (2)H in feathers and with wing-tip shape, showing that individuals from different geographic origins display a degree of ecological segregation in shared winter quarters. Isotopic mixing models indicate that wintering birds originating from more northerly populations consume more invertebrates. Our multi-scale study suggests that trophic-niche segregation may result from specializations (arising in the population-specific breeding areas) that are transported by the migrants into the shared wintering grounds.

Large-scale neural dynamics: simple and complex

We review the use of neural field models for modelling the brain at the large scales necessary for interpreting EEG, fMRI, MEG and optical imaging data. Albeit a framework that is limited to coarse-grained or mean-field activity, neural field models provide a framework for unifying data from different imaging modalities. Starting with a description of neural mass models we build to spatially extended cortical models of layered two-dimensional sheets with long range axonal connections mediating synaptic interactions. Reformulations of the fundamental non-local mathematical model in terms of more familiar local differential (brain wave) equations are described. Techniques for the analysis of such models, including how to determine the onset of spatio-temporal pattern forming instabilities, are reviewed. Extensions of the basic formalism to treat refractoriness, adaptive feedback and inhomogeneous connectivity are described along with open challenges for the development of multi-scale models that can integrate macroscopic models at large spatial scales with models at the microscopic scale.

Statistical Analysis and Modelling Aspects of Thermally Driven Turbulence

The present work aims to provide a deeper understanding of thermally driven turbulence and to address some modelling aspects related to the physics of the flow. For this purpose, two idealized systems are investigated by Direct Numerical Simulation: the rotating and non-rotating Rayleigh-Bénard convection. The preliminary study of the flow topologies shows how the coherent structures organise into different patterns depending on the rotation rate. From a statistical perspective, the analysis of the turbulent kinetic energy and temperature variance budgets allows to identify the flow regions where the production, the transport, and the dissipation of turbulent fluctuations occur. To provide a multi-scale description of the flows, a theoretical framework based on the Kolmogorov and Yaglom equations is applied for the first time to the Rayleigh-Bénard convection. The analysis shows how the spatial inhomogeneity modulates the dynamics at different scales and wall-distances. Inside the core of the flow, the space of scales can be divided into an inhomogeneity-dominated range at large scales, an inertial-like range at intermediate scales and a dissipative range at small scales. This classic scenario breaks close to the walls, where the inhomogeneous mechanisms and the viscous/diffusive processes are important at every scale and entail more complex dynamics. The same theoretical framework is extended to the filtered velocity and temperature fields of non-rotating Rayleigh-Bénard convection. The analysis of the filtered Kolmogorov and Yaglom equations reveals the influence of the residual scales on the filtered dynamics both in physical and scale space, highlighting the effect of the relative position between the filter length and the crossover that separates the inhomogeneity-dominated range from the quasi-homogeneous range. The assessment of the filtered and residual physics results to be instrumental for the correct use of the existing Large-Eddy Simulation models and for the development of new ones.

Intelligent Sensor Systems for Structural Health Monitoring Applications

The convergence between the recent developments in sensing technologies, data science, signal processing and advanced modelling has fostered a new paradigm to the Structural Health Monitoring (SHM) of engineered structures, which is the one based on intelligent sensors, i.e., embedded devices capable of stream processing data and/or performing structural inference in a self-contained and near-sensor manner. To efficiently exploit these intelligent sensor units for full-scale structural assessment, a joint effort is required to deal with instrumental aspects related to signal acquisition, conditioning and digitalization, and those pertaining to data management, data analytics and information sharing. In this framework, the main goal of this Thesis is to tackle the multi-faceted nature of the monitoring process, via a full-scale optimization of the hardware and software resources involved by the {SHM} system. The pursuit of this objective has required the investigation of both: i) transversal aspects common to multiple application domains at different abstraction levels (such as knowledge distillation, networking solutions, microsystem {HW} architectures), and ii) the specificities of the monitoring methodologies (vibrations, guided waves, acoustic emission monitoring). The key tools adopted in the proposed monitoring frameworks belong to the embedded signal processing field: namely, graph signal processing, compressed sensing, ARMA System Identification, digital data communication and TinyML.

Development of machine learning methods for multi-modal biomarkers detection and integration

In medicine, innovation depends on a better knowledge of the human body mechanism, which represents a complex system of multi-scale constituents. Unraveling the complexity underneath diseases proves to be challenging. A deep understanding of the inner workings comes with dealing with many heterogeneous information. Exploring the molecular status and the organization of genes, proteins, metabolites provides insights on what is driving a disease, from aggressiveness to curability. Molecular constituents, however, are only the building blocks of the human body and cannot currently tell the whole story of diseases. This is why nowadays attention is growing towards the contemporary exploitation of multi-scale information. Holistic methods are then drawing interest to address the problem of integrating heterogeneous data. The heterogeneity may derive from the diversity across data types and from the diversity within diseases. Here, four studies conducted data integration using customly designed workflows that implement novel methods and views to tackle the heterogeneous characterization of diseases. The first study devoted to determine shared gene regulatory signatures for onco-hematology and it showed partial co-regulation across blood-related diseases. The second study focused on Acute Myeloid Leukemia and refined the unsupervised integration of genomic alterations, which turned out to better resemble clinical practice. In the third study, network integration for artherosclerosis demonstrated, as a proof of concept, the impact of network intelligibility when it comes to model heterogeneous data, which showed to accelerate the identification of new potential pharmaceutical targets. Lastly, the fourth study introduced a new method to integrate multiple data types in a unique latent heterogeneous-representation that facilitated the selection of important data types to predict the tumour stage of invasive ductal carcinoma. The results of these four studies laid the groundwork to ease the detection of new biomarkers ultimately beneficial to medical practice and to the ever-growing field of Personalized Medicine.

Complexity of human postural control in young and older adults during prolonged standing

Aging is known to have a degrading influence on many structures and functions of the human sensorimotor system. The present work assessed aging-related changes in postural sway using fractal and complexity measures of the center of pressure (COP) dynamics with the hypothesis that complexity and fractality decreases in the older individuals. Older subjects (68 +/- 4 years) and young adult subjects (28 +/- 7 years) performed a quiet stance task (60 s) and a prolonged standing task (30 min) where subjects were allowed to move freely. Long-range correlations (fractality) of the data were estimated by the detrended fluctuation analysis (DFA); changes in entropy were estimated by the multi-scale entropy (MSE) measure. The DFA results showed that the fractal dimension was lower for the older subjects in comparison to the young adults but the fractal dimensions of both groups were not different from a 1/f noise, for time intervals between 10 and 600 s. The MSE analysis performed with the typically applied adjustment to the criterion distance showed a higher degree of complexity in the older subjects, which is inconsistent with the hypothesis that complexity in the human physiological system decreases with aging. The same MSE analysis performed without adjustment showed no differences between the groups. Taken all results together, the decrease in total postural sway and long-range correlations in older individuals are signs of an adaptation process reflecting the diminishing ability to generate adequate responses on a longer time scale.

Determination of coalescence kernels for high-shear granulation using DEM simulations

Discrete element method (DEM) modeling is used in parallel with a model for coalescence of deformable surface wet granules. This produces a method capable of predicting both collision rates and coalescence efficiencies for use in derivation of an overall coalescence kernel. These coalescence kernels can then be used in computationally efficient meso-scale models such as population balance equation (PBE) models. A soft-sphere DEM model using periodic boundary conditions and a unique boxing scheme was utilized to simulate particle flow inside a high-shear mixer. Analysis of the simulation results provided collision frequency, aggregation frequency, kinetic energy, coalescence efficiency and compaction rates for the granulation process. This information can be used to bridge the gap in multi-scale modeling of granulation processes between the micro-scale DEM/coalescence modeling approach and a meso-scale PBE modeling approach.

Integrating high and moderate spatial resolution image data to estimate forest age structure

The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).

Semi-automatic 3D Segmentation Of Costal Cartilage In CT Data From Pectus Excavatum Patients

One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69±0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.

Application of ionic liquids and enzymes for the removal of proteinaceous layers from polychrome of works of art and evaluation of the cleaning effectiveness

Dissertação Apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Ciências da Conservação, especialização em Pintura

Implementation of a probabilistic based framework for safety assessment of existing timber elements

The assessment of existing timber structures is often limited to information obtained from non or semi destructive testing, as mechanical testing is in many cases not possible due to its destructive nature. Therefore, the available data provides only an indirect measurement of the reference mechanical properties of timber elements, often obtained through empirical based correlations. Moreover, the data must result from the combination of different tests, as to provide a reliable source of information for a structural analysis. Even if general guidelines are available for each typology of testing, there is still a need for a global methodology allowing to combine information from different sources and infer upon that information in a decision process. In this scope, the present work presents the implementation of a probabilistic based framework for safety assessment of existing timber elements. This methodology combines information gathered in different scales and follows a probabilistic framework allowing for the structural assessment of existing timber elements with possibility of inference and updating of its mechanical properties, through Bayesian methods. The probabilistic based framework is based in four main steps: (i) scale of information; (ii) measurement data; (iii) probability assignment; and (iv) structural analysis. In this work, the proposed methodology is implemented in a case study. Data was obtained through a multi-scale experimental campaign made to old chestnut timber beams accounting correlations of non and semi-destructive tests with mechanical properties. Finally, different inference scenarios are discussed aiming at the characterization of the safety level of the elements.

Going beyond energy intensity to understand the energy metabolism of nations: the case of Argentina

The link between energy consumption and economic growth has been widely studied in the economic literature. Understanding this relationship is important from both an environmental and a socio-economic point of view, as energy consumption is crucial to economic activity and human environmental impact. This relevance is even higher for developing countries, since energy consumption per unit of output varies through the phases of development, increasing from an agricultural stage to an industrial one and then decreasing for certain service based economies. In the Argentinean case, the relevance of energy consumption to economic development seems to be particularly important. While energy intensity seems to exhibit a U-Shaped curve from 1990 to 2003 decreasing slightly after that year, total energy consumption increases along the period of analysis. Why does this happen? How can we relate this result with the sustainability debate? All these questions are very important due to Argentinean hydrocarbons dependence and due to the recent reduction in oil and natural gas reserves, which can lead to a lack of security of supply. In this paper we study Argentinean energy consumption pattern for the period 1990-2007, to discuss current and future energy and economic sustainability. To this purpose, we developed a conventional analysis, studying energy intensity, and a non conventional analysis, using the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) accounting methodology. Both methodologies show that the development process followed by Argentina has not been good enough to assure sustainability in the long term. Instead of improving energy use, energy intensity has increased. The current composition of its energy mix, and the recent economic crisis in Argentina, as well as its development path, are some of the possible explanations.

Characterization of lead-recycling facility emissions at various workplaces : major insights for sanitary risks assessment

Most available studies on lead smelter emissions deal with the environmental impact of outdoor particles, but only a few focus on air quality at workplaces. The objective of this study is to physically and chemically characterize the Pb-rich particles emitted at different workplaces in a lead recycling plant. A multi-scale characterization was conducted from bulk analysis to the level of individual particles, to assess the particles properties in relation with Pb speciation and availability. Process PM from various origins were sampled and then compared; namely Furnace and Refining PM respectively present in the smelter and at refinery workplaces, Emissions PM present in channeled emissions.These particles first differed by their morphology and size distribution, with finer particles found in emissions. Differences observed in chemical composition could be explained by the industrial processes. All PM contained the same major phases (Pb, PbS, PbO, PbSO4 and PbO·PbSO4) but differed on the nature and amount of minor phases. Due to high content in PM, Pb concentrations in the CaCl2 extractant reached relatively high values (40 mg.L-1). However, the ratios (soluble/total) of CaCl2 exchangeable Pb were relatively low (< 0.02%) in comparison with Cd (up to 18%). These results highlight the interest to assess the soluble fractions of all metals (minor and major) and discuss both total metal concentrations and ratios for risk evaluations. In most cases metal extractability increased with decreasing size of particles, in particular, lead exchangeability was highest for channeled emissions. Such type of study could help in the choice of targeted sanitary protection procedures and for further toxicological investigations. In the present context, particular attention is given to Emissions and Furnace PM. Moreover, exposure to other metals than Pb should be considered. [Authors]

Multiscale assessment of plant diversity in wooded pastures of the Jura mountains

Résumé La diminution de la biodiversité, à toutes les échelles spatiales et sur l'ensemble de la planète, compte parmi les problèmes les plus préoccupants de notre époque. En terme de conservation, il est aujourd'hui primordial de mieux comprendre les mécanismes qui créent et maintiennent la biodiversité dans les écosystèmes naturels ou anthropiques. La présente étude a pour principal objectif d'améliorer notre compréhension des patrons de biodiversité végétale et des mécanismes sous jacents, dans un écosystème complexe, riche en espèces et à forte valeur patrimoniale, les pâturages boisés jurassiens. Structure et échelle spatiales sont progressivement reconnues comme des dimensions incontournables dans l'étude des patrons de biodiversité. De plus, ces deux éléments jouent un rôle central dans plusieurs théories écologiques. Toutefois, peu d'hypothèses issues de simulations ou d'études théoriques concernant le lien entre structure spatiale du paysage et biodiversité ont été testées de façon empirique. De même, l'influence des différentes composantes de l'échelle spatiale sur les patrons de biodiversité est méconnue. Cette étude vise donc à tester quelques-unes de ces hypothèses et à explorer les patrons spatiaux de biodiversité dans un contexte multi-échelle, pour différentes mesures de biodiversité (richesse et composition en espèces) à l'aide de données de terrain. Ces données ont été collectées selon un plan d'échantillonnage hiérarchique. Dans un premier temps, nous avons testé l'hypothèse élémentaire selon laquelle la richesse spécifique (le nombre d'espèces sur une surface donnée) est liée à l'hétérogénéité environnementale quelque soit l'échelle. Nous avons décomposé l'hétérogénéité environnementale en deux parties, la variabilité des conditions environnementales et sa configuration spatiale. Nous avons montré que, en général, la richesse spécifique augmentait avec l'hétérogénéité de l'environnement : elle augmentait avec le nombre de types d'habitats et diminuait avec l'agrégation spatiale de ces habitats. Ces effets ont été observés à toutes les échelles mais leur nature variait en fonction de l'échelle, suggérant une modification des mécanismes. Dans un deuxième temps, la structure spatiale de la composition en espèces a été décomposée en relation avec 20 variables environnementales et 11 traits d'espèces. Nous avons utilisé la technique de partition de la variation et un descripteur spatial, récemment développé, donnant accès à une large gamme d'échelles spatiales. Nos résultats ont montré que la structure spatiale de la composition en espèces végétales était principalement liée à la topographie, aux échelles les plus grossières, et à la disponibilité en lumière, aux échelles les plus fines. La fraction non-environnementale de la variation spatiale de la composition spécifique avait une relation complexe avec plusieurs traits d'espèces suggérant un lien avec des processus biologiques tels que la dispersion, dépendant de l'échelle spatiale. Dans un dernier temps, nous avons testé, à plusieurs échelles spatiales, les relations entre trois composantes de la biodiversité : la richesse spécifique totale d'un échantillon (diversité gamma), la richesse spécifique moyenne (diversité alpha), mesurée sur des sous-échantillons, et les différences de composition spécifique entre les sous-échantillons (diversité beta). Les relations deux à deux entre les diversités alpha, beta et gamma ne suivaient pas les relations attendues, tout du moins à certaines échelles spatiales. Plusieurs de ces relations étaient fortement dépendantes de l'échelle. Nos résultats ont mis en évidence l'importance du rapport d'échelle (rapport entre la taille de l'échantillon et du sous-échantillon) lors de l'étude des patrons spatiaux de biodiversité. Ainsi, cette étude offre un nouvel aperçu des patrons spatiaux de biodiversité végétale et des mécanismes potentiels permettant la coexistence des espèces. Nos résultats suggèrent que les patrons de biodiversité ne peuvent être expliqués par une seule théorie, mais plutôt par une combinaison de théories. Ils ont également mis en évidence le rôle essentiel joué par la structure spatiale dans la détermination de la biodiversité, quelque soit le composant de la biodiversité considéré. Enfin, cette étude souligne l'importance de prendre en compte plusieurs échelles spatiales et différents constituants de l'échelle spatiale pour toute étude relative à la diversité spécifique. Abstract The world-wide loss of biodiversity at all scales has become a matter of urgent concern, and improving our understanding of local drivers of biodiversity in natural and anthropogenic ecosystems is now crucial for conservation. The main objective of this study was to further our comprehension of the driving forces controlling biodiversity patterns in a complex and diverse ecosystem of high conservation value, wooded pastures. Spatial pattern and scale are central to several ecological theories, and it is increasingly recognized that they must be taken -into consideration when studying biodiversity patterns. However, few hypotheses developed from simulations or theoretical studies have been tested using field data, and the evolution of biodiversity patterns with different scale components remains largely unknown. We test several such hypotheses and explore spatial patterns of biodiversity in a multi-scale context and using different measures of biodiversity (species richness and composition), with field data. Data were collected using a hierarchical sampling design. We first tested the simple hypothesis that species richness, the number of species in a given area, is related to environmental heterogeneity at all scales. We decomposed environmental heterogeneity into two parts: the variability of environmental conditions and its spatial configuration. We showed that species richness generally increased with environmental heterogeneity: species richness increased with increasing number of habitat types and with decreasing spatial aggregation of those habitats. Effects occurred at all scales but the nature of the effect changed with scale, suggesting a change in underlying mechanisms. We then decomposed the spatial structure of species composition in relation to environmental variables and species traits using variation partitioning and a recently developed spatial descriptor, allowing us to capture a wide range of spatial scales. We showed that the spatial structure of plant species composition was related to topography at the coarsest scales and insolation at finer scales. The non-environmental fraction of the spatial variation in species composition had a complex relationship with several species traits, suggesting a scale-dependent link to biological processes, particularly dispersal. Finally, we tested, at different spatial scales, the relationships between different components of biodiversity: total sample species richness (gamma diversity), mean species .richness (alpha diversity), measured in nested subsamples, and differences in species composition between subsamples (beta diversity). The pairwise relationships between alpha, beta and gamma diversity did not follow the expected patterns, at least at certain scales. Our result indicated a strong scale-dependency of several relationships, and highlighted the importance of the scale ratio when studying biodiversity patterns. Thus, our results bring new insights on the spatial patterns of biodiversity and the possible mechanisms allowing species coexistence. They suggest that biodiversity patterns cannot be explained by any single theory proposed in the literature, but a combination of theories is sufficient. Spatial structure plays a crucial role for all components of biodiversity. Results emphasize the importance of considering multiple spatial scales and multiple scale components when studying species diversity.

Pore-scale modeling of two-phase flow instabilities in porous media

Les problèmes d'écoulements multiphasiques en média poreux sont d'un grand intérêt pour de nombreuses applications scientifiques et techniques ; comme la séquestration de C02, l'extraction de pétrole et la dépollution des aquifères. La complexité intrinsèque des systèmes multiphasiques et l'hétérogénéité des formations géologiques sur des échelles multiples représentent un challenge majeur pour comprendre et modéliser les déplacements immiscibles dans les milieux poreux. Les descriptions à l'échelle supérieure basées sur la généralisation de l'équation de Darcy sont largement utilisées, mais ces méthodes sont sujettes à limitations pour les écoulements présentant de l'hystérèse. Les avancées récentes en terme de performances computationnelles et le développement de méthodes précises pour caractériser l'espace interstitiel ainsi que la distribution des phases ont favorisé l'utilisation de modèles qui permettent une résolution fine à l'échelle du pore. Ces modèles offrent un aperçu des caractéristiques de l'écoulement qui ne peuvent pas être facilement observées en laboratoire et peuvent être utilisé pour expliquer la différence entre les processus physiques et les modèles à l'échelle macroscopique existants. L'objet premier de la thèse se porte sur la simulation numérique directe : les équations de Navier-Stokes sont résolues dans l'espace interstitiel et la méthode du volume de fluide (VOF) est employée pour suivre l'évolution de l'interface. Dans VOF, la distribution des phases est décrite par une fonction fluide pour l'ensemble du domaine et des conditions aux bords particulières permettent la prise en compte des propriétés de mouillage du milieu poreux. Dans la première partie de la thèse, nous simulons le drainage dans une cellule Hele-Shaw 2D avec des obstacles cylindriques. Nous montrons que l'approche proposée est applicable même pour des ratios de densité et de viscosité très importants et permet de modéliser la transition entre déplacement stable et digitation visqueuse. Nous intéressons ensuite à l'interprétation de la pression capillaire à l'échelle macroscopique. Nous montrons que les techniques basées sur la moyenne spatiale de la pression présentent plusieurs limitations et sont imprécises en présence d'effets visqueux et de piégeage. Au contraire, une définition basée sur l'énergie permet de séparer les contributions capillaires des effets visqueux. La seconde partie de la thèse est consacrée à l'investigation des effets d'inertie associés aux reconfigurations irréversibles du ménisque causé par l'interface des instabilités. Comme prototype pour ces phénomènes, nous étudions d'abord la dynamique d'un ménisque dans un pore angulaire. Nous montrons que, dans un réseau de pores cubiques, les sauts et reconfigurations sont si fréquents que les effets d'inertie mènent à différentes configurations des fluides. A cause de la non-linéarité du problème, la distribution des fluides influence le travail des forces de pression, qui, à son tour, provoque une chute de pression dans la loi de Darcy. Cela suggère que ces phénomènes devraient être pris en compte lorsque que l'on décrit l'écoulement multiphasique en média poreux à l'échelle macroscopique. La dernière partie de la thèse s'attache à démontrer la validité de notre approche par une comparaison avec des expériences en laboratoire : un drainage instable dans un milieu poreux quasi 2D (une cellule Hele-Shaw avec des obstacles cylindriques). Plusieurs simulations sont tournées sous différentes conditions aux bords et en utilisant différents modèles (modèle intégré 2D et modèle 3D) afin de comparer certaines quantités macroscopiques avec les observations au laboratoire correspondantes. Malgré le challenge de modéliser des déplacements instables, où, par définition, de petites perturbations peuvent grandir sans fin, notre approche numérique apporte de résultats satisfaisants pour tous les cas étudiés. - Problems involving multiphase flow in porous media are of great interest in many scientific and engineering applications including Carbon Capture and Storage, oil recovery and groundwater remediation. The intrinsic complexity of multiphase systems and the multi scale heterogeneity of geological formations represent the major challenges to understand and model immiscible displacement in porous media. Upscaled descriptions based on generalization of Darcy's law are widely used, but they are subject to several limitations for flow that exhibit hysteric and history- dependent behaviors. Recent advances in high performance computing and the development of accurate methods to characterize pore space and phase distribution have fostered the use of models that allow sub-pore resolution. These models provide an insight on flow characteristics that cannot be easily achieved by laboratory experiments and can be used to explain the gap between physical processes and existing macro-scale models. We focus on direct numerical simulations: we solve the Navier-Stokes equations for mass and momentum conservation in the pore space and employ the Volume Of Fluid (VOF) method to track the evolution of the interface. In the VOF the distribution of the phases is described by a fluid function (whole-domain formulation) and special boundary conditions account for the wetting properties of the porous medium. In the first part of this thesis we simulate drainage in a 2-D Hele-Shaw cell filled with cylindrical obstacles. We show that the proposed approach can handle very large density and viscosity ratios and it is able to model the transition from stable displacement to viscous fingering. We then focus on the interpretation of the macroscopic capillary pressure showing that pressure average techniques are subject to several limitations and they are not accurate in presence of viscous effects and trapping. On the contrary an energy-based definition allows separating viscous and capillary contributions. In the second part of the thesis we investigate inertia effects associated with abrupt and irreversible reconfigurations of the menisci caused by interface instabilities. As a prototype of these phenomena we first consider the dynamics of a meniscus in an angular pore. We show that in a network of cubic pores, jumps and reconfigurations are so frequent that inertia effects lead to different fluid configurations. Due to the non-linearity of the problem, the distribution of the fluids influences the work done by pressure forces, which is in turn related to the pressure drop in Darcy's law. This suggests that these phenomena should be taken into account when upscaling multiphase flow in porous media. The last part of the thesis is devoted to proving the accuracy of the numerical approach by validation with experiments of unstable primary drainage in a quasi-2D porous medium (i.e., Hele-Shaw cell filled with cylindrical obstacles). We perform simulations under different boundary conditions and using different models (2-D integrated and full 3-D) and we compare several macroscopic quantities with the corresponding experiment. Despite the intrinsic challenges of modeling unstable displacement, where by definition small perturbations can grow without bounds, the numerical method gives satisfactory results for all the cases studied.