Modèles de connaissance à paramètres identifiables expérimentalement pour les systèmes de refroidissement dessiccatif couplés à un système solaire

La Centrale de traitement d Air par Dessiccation (CAD) offre un contrôle complet de la température et de l'humidité dans les locaux climatisés. Son élément clé est la roue dessicante qui permet la dessiccation de l air et une régénération continue. A travers cette étude, nous nous intéressons au développement d une méthodologie pour obtenir un modèle dynamique de la roue utilisable dans les algorithmes de contrôle avancés de la CAD. La roue dessicante peut être considérée comme un système de type multi-entrées/multi-sorties (MIMO). La seconde partie de ce mémoire concerne l'identification expérimentale des paramètres des modèles d état de la roue dessicante pour deux types de modèles : boîte noire et boîte grise. Dans le cas de la boîte noire, tous les paramètres du modèle sont identifiés expérimentalement. Dans le cas de la boîte grise, certains paramètres sont dérivés de considérations physiques et les paramètres restants sont identifiés en utilisant les mesures expérimentales des entrées et des sorties. Les paramètres du modèle boîte grise ont une signification physique. En comparaison avec les modèles boîte noire, les modèles boîte grises sont moins précis sur le domaine sur lequel les paramètres ont été identifiés, mais beaucoup plus précis en dehors de ce domaine. Comme les paramètres ont une signification physique, leurs valeurs ne varient pas de manière significative avec le point de fonctionnement utilisé pour l identification. Dans l approche boîte grise, les valeurs des paramètres obtenues pour les modèles linéaires sont presque identiques pour tous les modèles locaux du coté dessiccation et pour tous les modèles locaux du coté régénération ; cela nous a permis de considérer qu un modèle local est valable pour tout le domaine de variation des variables d entrée. Le modèle final de la roue dessicante se compose de deux modèles globaux : un pour le côté de la dessiccation et l'autre pour le côté de la régénération. La troisième partie de ce travail consiste dans l'identification des coefficients de transfert de masse et de chaleur au sein de la roue dessicante en utilisant un modèle boîte grise. Le coefficient de transfert de masse, le coefficient de transfert convectif et le nombre de Nusselt ont été obtenus en écrivant les paramètres du modèle d état en fonction d une seule variable et en exprimant les paramètres en fonction des caractéristiques géométriques et des propriétés de matériaux de la roue. Ce travail contribue au développement d un modèle d état utilisable pour la synthèse des algorithmes de contrôle pour la roue dessicante.Desiccant Air Unit (DAU) offers a complete control of air temperature and humidity in the conditioned space. Its key component is the desiccant wheel which provides the functions of air desiccation and regeneration. The aim of this study is to develop a methodology for obtaining a dynamic model of the desiccant wheel which can be used for the model-based control algorithms of DAU. The desiccant wheel can be regarded as a multi-input/multi-output (MIMO) system. The first part of the thesis is devoted to the modeling of the desiccant wheel based on energy and mass balance equations. The resulting set of equations is formulated as a second order state-space system without delay. The second part of this thesis concerns the experimental identification of the parameters of the state-space model of the desiccant wheel by using a black-box and a gray-box approach. In the case of the black-box, all the parameters of the model are identified experimentally. The identified parameters have values which minimize the difference between the output of the model and the experimental values. The parameters of the black-box model do not have physical significance. Although precise in the range of variation of the inputs in which the parameters were identified, this model gives significant errors in other domains of variation of the inputs. The parameters of the gray-box model are physically significant. Compared with the black-box models, the gray-box model was less accurate for the domains for which the parameters were identified, but it was notably more robust when applied to other ranges of the inputs. Since the parameters are related to physical properties, their values do not vary significantly with changes of the operating point used for identification. For the gray-box approach, the parameter values obtained for the linear models are almost identical for all local models on the desiccation side and all the local models on the regeneration side, suggesting that a local model may be valid for all the complete range of input variables. Using the above results, a final model of the desiccant wheel was developed, comprising two global models: one for the desiccation side and another for the regeneration side. The third part of the thesis deals with the identification of mass and heat transfer coefficients of the air within the desiccant wheel using a gray-box model. The mass transfer coefficient, the convective heat transfer coefficient and the Nusselt number were obtained by defining the variable parameters of the model as a function of a single variable and by expressing the constant parameters as a function of the geometric and material properties of the wheel. This work contributes to the development of a state-space model used for the synthesis of control algorithms for the desiccant wheel.VILLEURBANNE-DOC'INSA-Bib. elec. (692669901) / SudocSudocFranceF

Anxiety in Mice: A Principal Component Analysis Study

Two principal component analyses of anxiety were undertaken investigating two strains of mice (ABP/Le and C57BL/6ByJ) in two different experiments, both classical tests for assessing anxiety in rodents. The elevated plus-maze and staircase were used for the first experiment, and a free exploratory paradigm and light-dark discrimination were used for the second. The components in the analyses produced definitions of four fundamental behavior patterns: novelty-induced anxiety, general activity, exploratory behavior, and decision making. We also noted that the anxious phenotype was determined by both strain and experimental procedure. The relationship between behavior patterns and the use of specific tests plus links with the genetic background are discussed

Metasurface-enhanced Light Detection and Ranging Technology

Deploying advanced imaging solutions to robotic and autonomous systems by mimicking human vision requires simultaneous acquisition of multiple fields of views, named the peripheral and fovea regions. Low-resolution peripheral field provides coarse scene exploration to direct the eye to focus to a highly resolved fovea region for sharp imaging. Among 3D computer vision techniques, Light Detection and Ranging (LiDAR) is currently considered at the industrial level for robotic vision. LiDAR is an imaging technique that monitors pulses of light at optical frequencies to sense the space and to recover three-dimensional ranging information. Notwithstanding the efforts on LiDAR integration and optimization, commercially available devices have slow frame rate and low image resolution, notably limited by the performance of mechanical or slow solid-state deflection systems. Metasurfaces (MS) are versatile optical components that can distribute the optical power in desired regions of space. Here, we report on an advanced LiDAR technology that uses ultrafast low FoV deflectors cascaded with large area metasurfaces to achieve large FoV and simultaneous peripheral and central imaging zones. This technology achieves MHz frame rate for 2D imaging, and up to KHz for 3D imaging, with extremely large FoV (up to 150{\deg}deg. on both vertical and horizontal scanning axes). The use of this disruptive LiDAR technology with advanced learning algorithms offers perspectives to improve further the perception capabilities and decision-making process of autonomous vehicles and robotic systems.Comment: 25pages, 18 figures. Including supplementary material

Metasurface-enhanced light detection and ranging technology

: Deploying advanced imaging solutions to robotic and autonomous systems by mimicking human vision requires simultaneous acquisition of multiple fields of views, named the peripheral and fovea regions. Among 3D computer vision techniques, LiDAR is currently considered at the industrial level for robotic vision. Notwithstanding the efforts on LiDAR integration and optimization, commercially available devices have slow frame rate and low resolution, notably limited by the performance of mechanical or solid-state deflection systems. Metasurfaces are versatile optical components that can distribute the optical power in desired regions of space. Here, we report on an advanced LiDAR technology that leverages from ultrafast low FoV deflectors cascaded with large area metasurfaces to achieve large FoV (150°) and high framerate (kHz) which can provide simultaneous peripheral and central imaging zones. The use of our disruptive LiDAR technology with advanced learning algorithms offers perspectives to improve perception and decision-making process of ADAS and robotic systems

Metasurface-enhanced light detection and ranging technology

Deploying advanced imaging solutions to robotic and autonomous systems by mimicking human vision requires simultaneous acquisition of multiple fields of views, named the peripheral and fovea regions. Among 3D computer vision techniques, LiDAR is currently considered at the industrial level for robotic vision. Notwithstanding the efforts on LiDAR integration and optimization, commercially available devices have slow frame rate and low resolution, notably limited by the performance of mechanical or solid-state deflection systems. Metasurfaces are versatile optical components that can distribute the optical power in desired regions of space. Here, we report on an advanced LiDAR technology that leverages from ultrafast low FoV deflectors cascaded with large area metasurfaces to achieve large FoV (150°) and high framerate (kHz) which can provide simultaneous peripheral and central imaging zones. The use of our disruptive LiDAR technology with advanced learning algorithms offers perspectives to improve perception and decision-making process of ADAS and robotic systems

Plant-dominated assemblage and invertebrates from the lower Cenomanian of Jaunay-Clan, western France

International audienceTwo fossil localities are reported on the "LGV SEA" railroad from the Lower Cenomanianof Jaunay-Clan (JC), near Poitiers, western France. The laminated mudstones yielded plantfossils including ferns (Cladophlebis, Osmundophyllum, Ruffordia goeppertii, Sphenopteris),conifers (Brachyphyllum, Dammarophyllum, Pagiophyllum), and terrestrial and aquaticfreshwater angiosperms (Eucalyptolaurus depreii, Ploufolia). They are associated with acoleopteran insect that shows systematic affinities to the modern subfamily Chrysomeli-nae (Chrysomelidae). This assemblage suggests connections with arborescent vegetationgrowing in calm freshwater environment. Brackish to marine invertebrates also occurand include a dakoticancroid crab (Brachyura, Podotremata, Dakoticancroidea) and a fewbivalves (Brachidontes). They suggest brackish episodes during pond sedimentation in acoastal environment. Lastly, vertebrates are represented by an isolated feather

IRGM Is a Common Target of RNA Viruses that Subvert the Autophagy Network

Autophagy is a conserved degradative pathway used as a host defense mechanism against intracellular pathogens. However, several viruses can evade or subvert autophagy to insure their own replication. Nevertheless, the molecular details of viral interaction with autophagy remain largely unknown. We have determined the ability of 83 proteins of several families of RNA viruses (Paramyxoviridae, Flaviviridae, Orthomyxoviridae, Retroviridae and Togaviridae), to interact with 44 human autophagy-associated proteins using yeast two-hybrid and bioinformatic analysis. We found that the autophagy network is highly targeted by RNA viruses. Although central to autophagy, targeted proteins have also a high number of connections with proteins of other cellular functions. Interestingly, immunity-associated GTPase family M (IRGM), the most targeted protein, was found to interact with the autophagy-associated proteins ATG5, ATG10, MAP1CL3C and SH3GLB1. Strikingly, reduction of IRGM expression using small interfering RNA impairs both Measles virus (MeV), Hepatitis C virus (HCV) and human immunodeficiency virus-1 (HIV-1)-induced autophagy and viral particle production. Moreover we found that the expression of IRGM-interacting MeV-C, HCV-NS3 or HIV-NEF proteins per se is sufficient to induce autophagy, through an IRGM dependent pathway. Our work reveals an unexpected role of IRGM in virus-induced autophagy and suggests that several different families of RNA viruses may use common strategies to manipulate autophagy to improve viral infectivity

Convection naturelle instationnaire en milieu confine stratifie

SIGLECNRS T 58219 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Étude numérique d'écoulements turbulents à l'aide de la simulation des grandes structures (application à des écoulements de convection naturelle et mixte dans des cavités fermées ou ouvertes)

La Simulation des Grandes Structures (SGS) a été étudiée lors de cette thèse. L objectif de ce travail numérique consistait à tester la capacité de quelques modèles de sous-maille et plus particulièrement ceux associés aux approches dynamiques souvent utilisées dans la littérature, à reproduire, d'abord les écoulements de convection naturelle en espaces confinés, avant de passer à des situations plus réalistes faisant appel à des écoulements de type jet en convection forcée ou mixte dans des espaces ventilés, susceptibles d être rencontre s dans le domaine de l habitat. En convection naturelle dans une cavité fermée anisotherme, la SGS a permis de reproduire correctement les résultats numériques de référence d une Simulation Numérique Directe 2D et les comparaisons ont été encore plus proches en 3D. En convection forcée dans une cavité ventilée isotherme équipée d un soufflage et extraction d écoulement, la SGS 3D a permis de bien reproduire les résultats expérimentaux de l Annexe20 de l Agence Internationale de l Energie. Les résultats ont été encore améliorés par l introduction d une perturbation du jet au soufflage pour modéliser l intensité turbulente mesurée expérimentalement. En convection mixte dans une cavité ventilée anisotherme équipée d un soufflage et extraction d écoulement, avec un plancher chauffé, la SGS 3D montre un très bon accord avec une expérience réalisée au Laboratoire d'Etudes thermiques à Poitiers et reproduit également le comportement singulier de l écoulement (bifurcation et changement de direction avec phénomène d hystérésis) détecté expérimentalement. À notre connaissance, aucune étude numérique n a permis jusqu à présent une telle comparaison.LA ROCHELLE-BU (173002101) / SudocSudocFranceF