32 research outputs found

    Diamond-based models for scientific visualization

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    Hierarchical spatial decompositions are a basic modeling tool in a variety of application domains including scientific visualization, finite element analysis and shape modeling and analysis. A popular class of such approaches is based on the regular simplex bisection operator, which bisects simplices (e.g. line segments, triangles, tetrahedra) along the midpoint of a predetermined edge. Regular simplex bisection produces adaptive simplicial meshes of high geometric quality, while simplifying the extraction of crack-free, or conforming, approximations to the original dataset. Efficient multiresolution representations for such models have been achieved in 2D and 3D by clustering sets of simplices sharing the same bisection edge into structures called diamonds. In this thesis, we introduce several diamond-based approaches for scientific visualization. We first formalize the notion of diamonds in arbitrary dimensions in terms of two related simplicial decompositions of hypercubes. This enables us to enumerate the vertices, simplices, parents and children of a diamond. In particular, we identify the number of simplices involved in conforming updates to be factorial in the dimension and group these into a linear number of subclusters of simplices that are generated simultaneously. The latter form the basis for a compact pointerless representation for conforming meshes generated by regular simplex bisection and for efficiently navigating the topological connectivity of these meshes. Secondly, we introduce the supercube as a high-level primitive on such nested meshes based on the atomic units within the underlying triangulation grid. We propose the use of supercubes to associate information with coherent subsets of the full hierarchy and demonstrate the effectiveness of such a representation for modeling multiresolution terrain and volumetric datasets. Next, we introduce Isodiamond Hierarchies, a general framework for spatial access structures on a hierarchy of diamonds that exploits the implicit hierarchical and geometric relationships of the diamond model. We use an isodiamond hierarchy to encode irregular updates to a multiresolution isosurface or interval volume in terms of regular updates to diamonds. Finally, we consider nested hypercubic meshes, such as quadtrees, octrees and their higher dimensional analogues, through the lens of diamond hierarchies. This allows us to determine the relationships involved in generating balanced hypercubic meshes and to propose a compact pointerless representation of such meshes. We also provide a local diamond-based triangulation algorithm to generate high-quality conforming simplicial meshes

    Representation and Analysis of Topology in Multi-Representation Databases

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    A 3d geoscience information system framework

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    Two-dimensional geographical information systems are extensively used in the geosciences to create and analyse maps. However, these systems are unable to represent the Earth's subsurface in three spatial dimensions. The objective of this thesis is to overcome this deficiency, to provide a general framework for a 3d geoscience information system (GIS), and to contribute to the public discussion about the development of an infrastructure for geological observation data, geomodels, and geoservices. Following the objective, the requirements for a 3d GIS are analysed. According to the requirements, new geologically sensible query functionality for geometrical, topological and geological properties has been developed and the integration of 3d geological modeling and data management system components in a generic framework has been accomplished. The 3d geoscience information system framework presented here is characterized by the following features: - Storage of geological observation data and geomodels in a XML-database server. According to a new data model, geological observation data can be referenced by a set of geomodels. - Functionality for querying observation data and 3d geomodels based on their 3d geometrical, topological, material, and geological properties were developed and implemented as plug-in for a 3d geomodeling user application. - For database queries, the standard XML query language has been extended with 3d spatial operators. The spatial database query operations are computed using a XML application server which has been developed for this specific purpose. This technology allows sophisticated 3d spatial and geological database queries. Using the developed methods, queries can be answered like: "Select all sandstone horizons which are intersected by the set of faults F". This request contains a topological and a geological material parameter. The combination of queries with other GIS methods, like visual and statistical analysis, allows geoscience investigations in a novel 3d GIS environment. More generally, a 3d GIS enables geologists to read and understand a 3d digital geomodel analogously as they read a conventional 2d geological map

    Multi-GPU acceleration of a DGTD method for modeling human exposure to electromagnetic waves

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    We present a high performance computing methodology for the simulation of electromagnetic wave propagation in biological tissues and its application to the numerical evaluation of radio frequency absorption in head tissues as they are exposed to radiation from a cellular phone. For this purpose, the system of time-domain Maxwell equations is discretized in space by a discontinuous Galerkin method which is formulated on a tetrahedral mesh and which relies on a high order interpolation of the electromagnetic field components within a mesh element. The semi-discretized equations are then time integrated by a second order leap-frog scheme. The resulting numerical methodology is adapted to modern parallel computing systems with multiple GPU acceleration cards by adopting a hybrid strategy that combines a coarse grain SPMD programming model for inter-GPU parallelization and a fine grain SIMD programming model for intra-GPU parallelization. The performance improvement thanks to multiple-GPU acceleration is demonstrated through large-scale simulations that are performed on a cluster of GPUs using realistic heterogeneous models of head tissues built from medical images

    Finite element simulations: computations and applications to aerodynamics and biomedicine.

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    171 p.Las ecuaciones en derivadas parciales describen muchos fenómenos de interés práctico y sus solucionessuelen necesitar correr simulaciones muy costosas en clústers de cálculo.En el ámbito de los flujos turbulentos, en particular, el coste de las simulaciones es demasiado grande sise utilizan métodos básicos, por eso es necesario modelizar el sistema.Esta tesis doctoral trata principalmente de dos temas en Cálculo Científico.Por un lado, estudiamos nuevos desarrollos en la modelización y simulación de flujos turbulentos;utilizamos un Método de Elementos Finitos adaptativo y un modelo de ¿número de Reynolds infinito¿para reducir el coste computacional de simulaciones que, sin estas modificaciones, serían demasiadocostosas.De esta manera conseguimos lograr simulaciones evolutivas de flujos turbulentos con número deReynolds muy grande, lo cual se considera uno de los mayores retos en aerodinámica.El otro pilar de esta tesis es una aplicación biomédica.Desarrollamos un modelo computacional de Ablación (Cardiaca) por Radiofrecuencia, una terapiacomún para tratar varias enfermedades, por ejemplo algunas arritmias.Nuestro modelo mejora los modelos existentes en varias maneras, y en particular en tratar de obteneruna aproximación fiel de la geometría del sistema, lo cual se descubre ser crítico para simularcorrectamente la física del fenómeno

    Analyse de séries temporelles d’images à moyenne résolution spatiale : reconstruction de profils de LAI, démélangeage : application pour le suivi de la végétation sur des images MODIS

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    This PhD dissertation is concerned with time series analysis for medium spatial resolution (MSR) remote sensing images. The main advantage of MSR data is their high temporal rate which allows to monitor land use. However, two main problems arise with such data. First, because of cloud coverage and bad acquisition conditions, the resulting time series are often corrupted and not directly exploitable. Secondly, pixels in medium spatial resolution images are often “mixed” in the sense that the spectral response is a combination of the response of “pure” elements.These two problems are addressed in this PhD. First, we propose a data assimilation technique able to recover consistent time series of Leaf Area Index from corrupted MODIS sequences. To this end, a plant growth model, namely GreenLab, is used as a dynamical constraint. Second, we propose a new and efficient unmixing technique for time series. It is in particular based on the use of “elastic” kernels able to properly compare time series shifted in time or of various lengths.Experimental results are shown both on synthetic and real data and demonstrate the efficiency of the proposed methodologies.Cette thèse s’intéresse à l’analyse de séries temporelles d’images satellites à moyenne résolution spatiale. L’intérêt principal de telles données est leur haute répétitivité qui autorise des analyses de l’usage des sols. Cependant, deux problèmes principaux subsistent avec de telles données. En premier lieu, en raison de la couverture nuageuse, des mauvaises conditions d’acquisition, ..., ces données sont souvent très bruitées. Deuxièmement, les pixels associés à la moyenne résolution spatiale sont souvent “mixtes” dans la mesure où leur réponse spectrale est une combinaison de la réponse de plusieurs éléments “purs”. Ces deux problèmes sont abordés dans cette thèse. Premièrement, nous proposons une technique d’assimilation de données capable de recouvrer des séries temporelles cohérentes de LAI (Leaf Area Index) à partir de séquences d’images MODIS bruitées. Pour cela, le modèle de croissance de plantes GreenLab estutilisé. En second lieu, nous proposons une technique originale de démélangeage, qui s’appuie notamment sur des noyaux “élastiques” capables de gérer les spécificités des séries temporelles (séries de taille différentes, décalées dans le temps, ...)Les résultats expérimentaux, sur des données synthétiques et réelles, montrent de bonnes performances des méthodologies proposées
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