La simulation numérique des écoulements est une étape essentielle de la conception des turbines à gaz équipant les hélicoptères. La recherche permanente de la performance a conduit à des géométries de turbines très complexes et il devient de plus en plus difficile de modéliser des grilles de simulation qui épousent parfaitement la CAO des moteurs. La technique chimère permet de s’affranchir des contraintes de recollement parfait des différentes grilles en autorisant leur chevauchement. Cependant elle soulève de nouveaux problèmes lors de la phase de post-traitement, lorsqu’il s’agit d’exploiter les résultats de simulation afin de faire de nouveaux calculs ou de les visualiser, parce que les outils usuels ne sont pas adaptés à ces configurations particulières. Dans le cadre des deux premiers projets du programme MOSART du pôle de compétitivité Aerospace Valley, respectivement MACAO et OSMOSES, nous avons travaillé en collaboration avec l’entreprise Turbomeca à la conception d’une méthode de reconstruction volumique afin de traiter les résultats de simulations à base chimère. Nous avons ainsi proposé une méthode innovante permettant de reconstruire une partition de l’espace de simulation exempte de chevauchement entre grilles. La nouvelle partition conserve le maximum de propriétés des grilles d’origine et assure en tout point la conformité aux bords. La complexité théorique est linéaire avec la taille des grilles d’origine et nous permet d’obtenir des temps de traitement de l’ordre de la seconde pour des grilles de plusieurs centaines de milliers de mailles. Le principal intérêt de ce travail est de rendre exploitables les résultats de simulations à base chimère par les outils de post-traitement, qu’il s’agisse d’outils maison ou des nombreux logiciels commerciaux ou OpenSource disponibles, condition indispensable pour l’adoption de la méthode chimère par les bureaux d’études. / Computationnal fluid dynamics is an essential step in gas turbine modelling. Continuous optimization of turbines has led to sophisticated geometries, which raises severe issues for the design of adapted simulation grids. The chimera technique aims at relaxing geometry matching constraints by allowing grids overlap. However, post-processing of simulation results performed over chimera grids raises new issues because usual tools are not tuned for this particular geometricconfigurations. In the framework of the MOSART programme of the world competitiveness cluster Aerospace Valley, we have been working in collaboration with Turbomeca in order to develop a technique for the volumetric reconstruction of chimerasimulation results. We propose an innovative method that allows us to build a collection of non-overlapping grids while preserving the main properties of the former simulation grids and featuring boundary conforming property everywhere.The theorical complexity of our algorithms has proved to be linear in the size of the former grids and leads to computation times of a few seconds for grids of hundreds of thousands of cells. The main impact of this work leads in the possibility of using any post-processing tool, including a large number of OpenSource solutions, for post-processing chimera simulation results, which is a mandatory condition for the wide acceptance of this method by industry actors.

[pt] A reconstrução de cenas a partir de imagens tem recebido, recentemente, grande interesse por parte dos pesquisadores das áreas de visão computacional, computação gráfica e modelagem geométrica. Várias são as suas aplicações como, por exemplo, modelagem de objetos a partir de imagens, construção de ambientes virtuais e telepresença. Dentre os métodos que têm produzido bons resultados na reconstrução de cenas a partir de imagens, podemos destacar aqueles que se baseiam em algoritmos de Escultura do Espaço. Tais técnicas procuram determinar quais são os elementos, em uma representação volumétrica do espaço da cena, que satisfazem um conjunto de restrições fotométricas impostas por um conjunto de imagens. Uma vez determinados, tais elementos volumétricos são coloridos de modo que reproduzam as informações fotométricas nas imagens de entrada, com uma certa margem de tolerância especificada com base em critérios estatísticos. Neste trabalho, investigamos o emprego de técnicas utilizadas em visualização no desenvolvimento de métodos de escultura do espaço. Como resultado, propomos um método por refinamento adaptativo que trabalha sobre espaços de reconstrução representados através de subdivisões espaciais. Tal método é capaz de realizar o processo de reconstrução de modo mais eficiente, empregando esforços proporcionais às características locais da cena, que são descobertas à medida em que a reconstrução é realizada. Finalmente, avaliamos a qualidade e a eficiência do método proposto, com base em um conjunto de resultados obtidos através de um sistema de reconstrução de objetos que utiliza imagens capturadas por webcams. / [en] The reconstruction of scenes from imagens has received special attention from researchers of the areas of computer vision, computer graphics and geometric modeling. As examples of application we can mention image-based scene reconstruction, modeling of complex as-built objects, construction of virtual environments and telepresence. Among the most successful methods used for the reconstruction of scenes from images are those based on Space Carving algorithms. These techniques reconstruct the shape of the objects of interest in a scene by determining, in a volumetric representation of the scene space, those elements that satisfy a set of photometric constraints imposed by the input images. Once determined, each photo- consistent element is colorized according to the photometric information in the input images, in such a way that they reproduce the photometric information in the input images, within some pre-specificied error tolerance. In this work, we investigate the use of rendering techniques in space carving methods. As a result, we propose a method based on an adaptive refinement process which works on reconstruction spaces represented by spatial subdivisions. We claim that such method can reconstruct the objects of interest in a more efficient way, using resources proportional to the local characteristics of the scene, which are discovered as the reconstruction takes place. Finally, we evaluate the quality and the efficiency of the method based on the results obtained from a reconstruction device that works with images captured from webcams.