Assimilation de données pour les problèmes non-Gaussiens : méthodologie et applications à la biogéochimie marine

Data assimilation for Geosciences is a discipline seeking to improve our knowledge of a physical system based on the information from numerical models simulating this system and the information from the measures observing this system. The data assimilation methods traditionally used (eg the 4DVAR or the ensemble Kalman filters) are based on assumptions of Gaussianity of the probabilities involved and linearity of the models. With the increasing complexity of models and observation networks, these assumptions are increasingly unjustified and therefore penalizing. This complexity is particularly strong in oceanography coupled with marine biogeochemistry.The objectives of this thesis are to understand the appearance of non Gaussianity in an estimation problem, to think out a data assimilation method adapted to highly non Gaussian problems and, in the coupling of ocean dynamics and marine biogeochemistry, to explore the relevance of the use of non Gaussian methods.At first, a methodological study is conducted. This study, supported by illustrations with the three variable Lorenz model, allows to highlight the limitations of traditional methods when facing non Gaussian problems. This study led to the development of a fully non Gaussian data assimilation filter : the Multivariate Rank Histogram Filter (MRHF).It is shown that the MRHF is efficient in highly non Gaussian regimes (including in a bimodal regime) for a relatively small number of members.Secondly, a numerical study is conducted. This study is conducted with twin experiments based on a 1D vertical model, ModECOGeL, coupling dynamics and biogeochemistry in the Ligurian Sea. We simulate different observation networks combining in situ profiles and satellite data. Several data assimilation methods are then compared using advanced ensemble evaluation diagnoses.Our experiments show the impact of observation networks and controled variables on the degree of non Gaussianity in an estimation problem. The control of the dynamic part of the model by observations of the dynamics at different frequencies is a quasi Gaussian problem, which a least squared filter such as the Ensemble Transform Kalman Filter solves well. In contrast, for the same observations, the control of biogeochemistry proves to be a non Gaussian problem and requires the use of a non Gaussian filter. Finally, it is shown that assimilation of ocean color data, for the joint control of the dynamic and the biogeochemistry, is improved by methods adapted for non Gaussianities such as the Anamorphosed Ensemble Kalman Filter. In addition, increasing the ocean color observation frequency makes unavoidable the use of fundamentally non Gaussian filters such as the MRHF.L'assimilation de données pour les géosciences est une discipline cherchant à améliorer notre connaissance d'un système physique en se basant sur l'information issue de modèles numériques simulant ce système et sur l'information issue des mesures observant ce système. Les méthodes d'assimilation de données traditionnellement utilisées (e.g. le 4DVar ou les filtres de Kalman d'ensemble) reposent sur des hypothèses de Gaussianité des probabilités en jeu et de linéarité des modèles. Avec la complexification des modèles et des réseaux d'observations, ces hypothèses sont de plus en plus injustifiées et donc pénalisantes. Cette complexification est particulièrement forte en océanographie couplée à la biogéochimie marine.Les objectifs de cette thèse sont de mieux comprendre l'apparition des non-Gaussianités dans un problème d'estimation, d'envisager une méthode d'assimilation de données adaptée aux problèmes fortement non-Gaussiens et, dans le cadre du couplage de la dynamique océanique et de la biogéochimie marine, d'explorer la pertinence de l'utilisation de méthodes non-Gaussiennes.Dans un premier temps, une étude méthodologique est conduite. Cette étude, appuyé par des illustrations avec le modèle de Lorenz à trois variables, permet de mettre en évidence les limitations des méthodes traditionnellement utilisées, face à des problèmes non-Gaussiens. Cette étude aboutit sur le développement d'un filtre d'assimilation de données d'ensemble entièrement non-Gaussien : le Multivariate Rank Histogram Filter (MRHF).Il est montré que le MRHF est performant dans des régimes fortement non-Gaussiens (notamment dans un régime bimodal) pour un nombre de membres relativement faible.Dans un second temps, une étude numérique est conduite. Cette étude est réalisée aux travers d'expériences jumelles basées sur un modèle vertical 1D, ModECOGeL, couplant la dynamique et la biogéochimie en mer Ligure. Nous simulons différents réseaux d'observations combinant des profils in situ et des données satellites. Plusieurs méthodes d'assimilation sont alors comparées à l'aide de diagnostics d'évaluation d'ensemble avancés.Nos expériences montrent l'impact du réseau d'observations et des variables de contrôle, sur le degré de non-Gaussianité d'un problème d'estimation. Le contrôle de la partie dynamique du modèle par des observations de la dynamique à différentes fréquences est un problème quasi-Gaussien, qu'un filtre aux moindres carrés, tel l'Ensemble Transform Kalman Filter, résout bien. En revanche pour ces mêmes observations, le contrôle de la biogéochimie s'avère être un problème non-Gaussien et nécessite l'utilisation d'un filtre non-Gaussien.Enfin, il est montré que l'assimilation de la couleur de l'eau, pour le contrôle mixte de la dynamique et de la biogéochimie, est améliorée par des méthodes adaptées aux non-Gaussianités, tel l'Ensemble Kalman Filter anamorphosé. De plus, l'augmentation de la fréquence d'observation de la couleur de l'eau rend incontournable l'utilisation de filtres fondamentalement non-Gaussiens comme le MRHF

Fluid Manipulation Using Thermoexpandable Polymer Based on Ploydimethylsiloxane and Expancel

Nowadays, manipulation of liquids in miniaturised environments finds applications in many fields in biology and medicine such as diagnostics, toxicity analysis, drug delivery and so on. In those domains, the use of disposable devices has the great advantage of removing any surface contamination which could results in device malfunction. In this context, the present work revolves around the use of a thermoexpandable material, composed of expandable beads in an elastomeric matrix, used as actuator for liquids. This material is expandable only once, providing a good actuation for disposable devices. It also allows to keep the material inflated without additional energy input. This thesis has three main goals: understanding the expansion properties of this material through characterisation and modelling, proposing implementation of the heating source, and investigating possible applications. Characterisation of the material reviews its capability to create movement. The two main parameters characterised are the volumetric expansion of the material and the pressure it can provide. To better understand those behaviours, a morphological study of Expancel® beads is also undertaken. Expansion of the composite is then theoretically modelled to provide a tool for future designs. The following part of this thesis focuses on solutions to implement the material for liquid actuation. Before this investigation, the main solution used to heat the material was the resistive heating of copper tracks on a circuit board. Here, alternative solutions are provided such as the use of clean room facilities, screen-printing and polymeric conductors. The pros and cons of the proposed solutions are stated in a way to allow the reader to choose the best option for his application. Finally, some applications of this actuation system are implemented and tested to highlight the limitations and advantages of this technology when put into application

The integration of photovoltaic panels system in net-zero energy buildings under Mediterranean climate

From an ecological perspective, sustainability alternatives require, on the one hand, the reduction ofenergy consumption and, on the other hand, taking advantage of so-called renewable primary energiessuch as: solar, wind, hydraulic, geothermal energy., biomass, etc. Among these so-called clean energyresources, solar energy is available at all levels of the earth. Through this study, we will try to highlight the importance and effectiveness of solar energy as arelevant alternative to integrate into the net zero energy architectural design process that aims to use solar energy to power the energy needs of a building while ensuring that the latter only consumes the energy it produces. The goal is to minimize dependence on external energy sources and maximize the use of renewable energy sources to obtain a self-sufficient, net-zero energy building. The aim of this research is firstly to assess the feasibility and effectiveness of integrating these systems, and secondly to evaluate the economic and environmental benefits of using them. This paper carried out an experimental study on the integration of a photovoltaic system within a cultural centre. The objective is to study the impact of this installation on the building's annual energy consumption, and the possibility of making the building a zero-energy building by installing a photovoltaic system. This was done using Retscreen clean energy awareness software. According to the results, the photovoltaic system integrated into the project generates 961,847.20 kWh of electricity per year, covering 74.33% of the building's annual electricity consumption. This reduces the annual electricity bill by 25%

Le café Soleil, la face cachée de l’astre

Depuis deux ans, ils travaillent sur un projet documentaire intitulé : Une journée au Soleil. L’idée est d’associer l’histoire de l’immigration algérienne, et plus particulièrement kabyle, à un lieu à la fois pratique et symbolique. Le Soleil est un café situé au 136, boulevard de Ménilmontant dans le XXe arrondissement de Paris. En tant que substitut du village d’origine, il assure cette fonction de refuge où persiste le passé, mais il sait aussi s’adapter aux évolutions sociétales

Fgf15 Neurons of the Dorsomedial Hypothalamus Control Glucagon Secretion and Hepatic Gluconeogenesis.

The counterregulatory response to hypoglycemia is an essential survival function. It is controlled by an integrated network of glucose-responsive neurons, which trigger endogenous glucose production to restore normoglycemia. The complexity of this glucoregulatory network is, however, only partly characterized. In a genetic screen of a panel of recombinant inbred mice we previously identified Fgf15, expressed in neurons of the dorsomedial hypothalamus (DMH), as a negative regulator of glucagon secretion. Here, we report on the generation of Fgf15 <sup>CretdTomato</sup> mice and their use to further characterize these neurons. We show that they were glutamatergic and comprised glucose-inhibited and glucose-excited neurons. When activated by chemogenetics, Fgf15 neurons prevented the increase in vagal nerve firing and the secretion of glucagon normally triggered by insulin-induced hypoglycemia. On the other hand, they increased the activity of the sympathetic nerve in the basal state and prevented its silencing by glucose overload. Higher sympathetic tone increased hepatic Creb1 phosphorylation, Pck1 mRNA expression, and hepatic glucose production leading to glucose intolerance. Thus, Fgf15 neurons of the DMH participate in the counterregulatory response to hypoglycemia by a direct adrenergic stimulation of hepatic glucose production while suppressing vagally induced glucagon secretion. This study provides new insights into the complex neuronal network that prevents the development of hypoglycemia