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La géométrie aléatoire pour la caractérisation de populations denses de particules : application aux écoulements diphasiques.
No full textThis thesis aims at developing a new approach for geometric modeling of two-phase flows, from 2D images of orthogonal projections, with the objective of extracting 3D morphological characteristics of the particles. The study mainly addresses the case of droplets and bubbles of spherical and ellipsoidal shape. Among the existing methods to deal with 2D images resulting from the projection of a 3D particles system, the pattern recognition and segmentation ones are the most common. However, they present major limitations. To overcome these problems, a 3D stochastic geometrical model (a marked point process) is proposed. The model was fitted to the observed data thanks to a numerical optimization process. The method’s performance was evaluated on numerical simulations of 2D images resulting from projections of spherical and ellipsoidal particles of known geometry. The accuracy of the model to retrieve the 3D size and shape distribution of the particles was highlighted, even from high density images. Experimental validation was also performed based on fully characterized suspensions of PMMA balls, of different sizes. Finally, in order to characterize typical systems encountered in multiphase flow processes, the proposed approach was applied to a bubbly flow with different gas flow rates (i.e. for several sizes and densities of bubbles). This PhD work illustrates the relevance of stochastic geometrical modeling for the characterization of two-phase flows. It opens up wide perspectives, as e.g. the implementation of more flexible models to better describe the possible interactions (attractions/repulsions) between particles.Cette thèse a pour objectif le développement d’une nouvelle approche de modélisation géométrique 3D d’écoulements diphasiques à partir d’images 2D de projections orthogonales, afin de caractériser les systèmes de particules. L’étude porte sur des particules (ici des gouttelettes ou des bulles) de forme sphérique et ellipsoïdale. Parmi les méthodes existantes pour traiter des images 2D obtenues par projection d’un système de particules 3D, celles de reconnaissance de forme et de segmentation sont les plus utilisées. Cependant, ce type d’approche présente de fortes limitations. Pour pallier ces problèmes, un modèle géométrique aléatoire 3D (processus ponctuel marqué) est proposé. Dans le but d’ajuster le modèle aux données observées, une optimisation numérique est réalisée. Les performances de cette méthode sont évaluées via des simulations numériques d’images 2D issues de projections de particules sphériques et ellipsoïdales de géométrie connue. Les résultats montrent une bonne estimation de la morphologie 3D des particules. Une validation expérimentale est également réalisée sur un écoulement diphasique contrôlé composé d’un mélange, connu, de billes de PMMA de différentes tailles. Finalement, dans le but de caractériser des écoulements classiquement rencontrés en mécanique des fluides, l’approche est appliquée à un écoulement gaz/liquide avec différents débits de gaz. Ce travail de thèse montre l’intérêt de la modélisation géométrique aléatoire pour la caractérisation d’écoulements diphasiques et ouvre de larges perspectives sur l’étude de modèles plus flexibles permettant de contrôler des interactions (attractions/répulsions) entre particules
3D geometrical characterization of populations of particles by stochastic geometry and image analysis : application to two-phase flows
No full textCette thèse a pour objectif le développement d’une nouvelle approche de modélisation géométrique 3D d’écoulements diphasiques à partir d’images 2D de projections orthogonales, afin de caractériser les systèmes de particules. L’étude porte sur des particules (ici des gouttelettes ou des bulles) de forme sphérique et ellipsoïdale. Parmi les méthodes existantes pour traiter des images 2D obtenues par projection d’un système de particules 3D, celles de reconnaissance de forme et de segmentation sont les plus utilisées. Cependant, ce type d’approche présente de fortes limitations. Pour pallier ces problèmes, un modèle géométrique aléatoire 3D (processus ponctuel marqué) est proposé. Dans le but d’ajuster le modèle aux données observées, une optimisation numérique est réalisée. Les performances de cette méthode sont évaluées via des simulations numériques d’images 2D issues de projections de particules sphériques et ellipsoïdales de géométrie connue. Les résultats montrent une bonne estimation de la morphologie 3D des particules. Une validation expérimentale est également réalisée sur un écoulement diphasique contrôlé composé d’un mélange, connu, de billes de PMMA de différentes tailles. Finalement, dans le but de caractériser des écoulements classiquement rencontrés en mécanique des fluides, l’approche est appliquée à un écoulement gaz/liquide avec différents débits de gaz. Ce travail de thèse montre l’intérêt de la modélisation géométrique aléatoire pour la caractérisation d’écoulements diphasiques et ouvre de larges perspectives sur l’étude de modèles plus flexibles permettant de contrôler des interactions (attractions/répulsions) entre particules.This thesis aims at developing a new approach for geometric modeling of two-phase flows, from 2D images of orthogonal projections, with the objective of extracting 3D morphological characteristics of the particles. The study mainly addresses the case of droplets and bubbles of spherical and ellipsoidal shape. Among the existing methods to deal with 2D images resulting from the projection of a 3D particles system, the pattern recognition and segmentation ones are the most common. However, they present major limitations. To overcome these problems, a 3D stochastic geometrical model (a marked point process) is proposed. The model was fitted to the observed data thanks to a numerical optimization process. The method’s performance was evaluated on numerical simulations of 2D images resulting from projections of spherical and ellipsoidal particles of known geometry. The accuracy of the model to retrieve the 3D size and shape distribution of the particles was highlighted, even from high density images. Experimental validation was also performed based on fully characterized suspensions of PMMA balls, of different sizes. Finally, in order to characterize typical systems encountered in multiphase flow processes, the proposed approach was applied to a bubbly flow with different gas flow rates (i.e. for several sizes and densities of bubbles). This PhD work illustrates the relevance of stochastic geometrical modeling for the characterization of two-phase flows. It opens up wide perspectives, as e.g. the implementation of more flexible models to better describe the possible interactions (attractions/repulsions) between particles
La géométrie aléatoire pour la caractérisation de populations denses de particules : application aux écoulements diphasiques.
No full textThis thesis aims at developing a new approach for geometric modeling of two-phase flows, from 2D images of orthogonal projections, with the objective of extracting 3D morphological characteristics of the particles. The study mainly addresses the case of droplets and bubbles of spherical and ellipsoidal shape. Among the existing methods to deal with 2D images resulting from the projection of a 3D particles system, the pattern recognition and segmentation ones are the most common. However, they present major limitations. To overcome these problems, a 3D stochastic geometrical model (a marked point process) is proposed. The model was fitted to the observed data thanks to a numerical optimization process. The method’s performance was evaluated on numerical simulations of 2D images resulting from projections of spherical and ellipsoidal particles of known geometry. The accuracy of the model to retrieve the 3D size and shape distribution of the particles was highlighted, even from high density images. Experimental validation was also performed based on fully characterized suspensions of PMMA balls, of different sizes. Finally, in order to characterize typical systems encountered in multiphase flow processes, the proposed approach was applied to a bubbly flow with different gas flow rates (i.e. for several sizes and densities of bubbles). This PhD work illustrates the relevance of stochastic geometrical modeling for the characterization of two-phase flows. It opens up wide perspectives, as e.g. the implementation of more flexible models to better describe the possible interactions (attractions/repulsions) between particles.Cette thèse a pour objectif le développement d’une nouvelle approche de modélisation géométrique 3D d’écoulements diphasiques à partir d’images 2D de projections orthogonales, afin de caractériser les systèmes de particules. L’étude porte sur des particules (ici des gouttelettes ou des bulles) de forme sphérique et ellipsoïdale. Parmi les méthodes existantes pour traiter des images 2D obtenues par projection d’un système de particules 3D, celles de reconnaissance de forme et de segmentation sont les plus utilisées. Cependant, ce type d’approche présente de fortes limitations. Pour pallier ces problèmes, un modèle géométrique aléatoire 3D (processus ponctuel marqué) est proposé. Dans le but d’ajuster le modèle aux données observées, une optimisation numérique est réalisée. Les performances de cette méthode sont évaluées via des simulations numériques d’images 2D issues de projections de particules sphériques et ellipsoïdales de géométrie connue. Les résultats montrent une bonne estimation de la morphologie 3D des particules. Une validation expérimentale est également réalisée sur un écoulement diphasique contrôlé composé d’un mélange, connu, de billes de PMMA de différentes tailles. Finalement, dans le but de caractériser des écoulements classiquement rencontrés en mécanique des fluides, l’approche est appliquée à un écoulement gaz/liquide avec différents débits de gaz. Ce travail de thèse montre l’intérêt de la modélisation géométrique aléatoire pour la caractérisation d’écoulements diphasiques et ouvre de larges perspectives sur l’étude de modèles plus flexibles permettant de contrôler des interactions (attractions/répulsions) entre particules
Stochastic geometry for 3D characterization of dense particle populations: application to two-phase flows
No full textMathieu De Langlard a remporté le prix de la meilleure thèse de l’ISSIA - Mathieu de Langlard, the winner of thePhD Competition in Stereology and Image Analysis _ Vidéoconférence - Keynote 4: First Commercial Dual MeV Energy X-ray CT for Container Inspection:System, Algorithm and Results - Mathieu De Langlard a remporté le prix de la meilleure thèse de l’ISSIAInternational audienc
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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