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<dc:title xml:lang="fr">Modélisation géostructurale 3D de parois rocheuses en milieu ferroviaire : application aux ouvrages en terre</dc:title>
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<dc:subject xml:lang="fr">Paroi rocheuse</dc:subject>
<dc:subject xml:lang="fr">Exploitation ferroviaire</dc:subject>
<dc:subject xml:lang="fr">Scanner-laser 3D</dc:subject>
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<dc:subject xml:lang="fr">Discontinuités rocheuses</dc:subject>
<dc:subject xml:lang="fr">Familles directionnelles</dc:subject>
<dc:subject xml:lang="fr">Analyse structurale</dc:subject>
<dc:subject xml:lang="fr">Classification automatique</dc:subject>
<dc:subject xml:lang="fr">Image solide</dc:subject>
<dc:subject xml:lang="en">Rock face</dc:subject>
<dc:subject xml:lang="en">Railway traffic</dc:subject>
<dc:subject xml:lang="en">Terrestrial laser scanner</dc:subject>
<dc:subject xml:lang="en">Dense image matching</dc:subject>
<dc:subject xml:lang="en">Rock discontinuity sets</dc:subject>
<dc:subject xml:lang="en">Strucutural analysis</dc:subject>
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<dcterms:abstract xml:lang="fr">Ce travail de thèse vise une optimisation des méthodologies de modélisation géostructurale, permettant d'aboutir à une meilleure gestion des aléas rocheux affectant le système ferroviaire. La caractérisation géométrique des massifs rocheux est entreprise grâce à une classification des modèles en sous-ensembles correspondant aux principales familles de discontinuités. En parallèle de cette caractérisation automatisée, une seconde approche dite manuelle a été examinée. Cette approche combine données tridimensionnelles (nuages de points denses) et support photographique (images 2D). Les données sur les discontinuités planaires, traditionnellement acquises manuellement en certains points nécessairement accessibles du massif, résultent désormais de l'analyse des modèles couvrant l'ensemble de l'ouvrage. Ce projet a permis le développement d'un outil de modélisation améliorant la connaissance du patrimoine rocheux sans engager la sécurité du personnel, ni la capacité de la ligne ferroviaire.</dcterms:abstract>
<dcterms:abstract xml:lang="en">This project aims at an optimization of geostructural modeling methodolgies, leading to a better knowledge and a better management of the rock risk impacting the railway system. Acquired 3D models are exploited in order ton convert 3D point clouds into geostructural analysis. Hence, we have developed a semi-automatic process that allows 3D models to be combined with the results of field surveys in order to provide more precise analyses of rock faces, for example, by classifying rock discontinuities into subsets according to their orientation. A second approach is proposed, combining both 3D point clouds (from LiDAR or image matching) and 2D digital images. Combining these high-quality data with the proposed automatic and manual processing method greatly improves the geometrical analysis of rock faces, increases the reliability of structural interpretations, and enables reinforcement procedures to be optimized.</dcterms:abstract>
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