The kinetic schemes, also known as Boltzmann schemes are based on the moment-method-strategy, where an upwind scheme is first developed at the Boltzmann level and after taking suitable moments we arrive at an upwind scheme for the governing Euler or Navier-Stokes equations. The Kinetic Flux Vector Splitting (KFVS)scheme, which belongs to the family of kinetic schemes is being extensively used to compute inviscid as well as viscous flows around many complex configurations of practical interest over the past two decades. To resolve many flow features accurately, like suction peak, minimising the loss in stagnation pressure, shocks, slipstreams, triple points, vortex sheets, shock-shock interaction, mixing layers, flow separation in viscous flows require an accurate and low dissipative numerical scheme. The first order KFVS method even though is very robust suffers from the problem of having much more numerical diffusion than required, resulting in very badly smearing of the above features. However, numerical dissipation can be reduced considerably by using higher order kinetic schemes. But they require more points in the stencil and hence consume more computational time and memory. The second order schemes require flux or slope limiters in the neighbourhood of discontinuities to avoid spurious and physically meaningless wiggles or oscillations in pressure, temperature or density. The limiters generally restrict the residue fall in second order schemes while in first order schemes residue falls up to machine zero. Further, pressure and density contours or streamlines are much smoother for first order accurate schemes than second order accurate schemes. A question naturally arises about the possibility of constructing first order upwind schemes which retain almost all advantages mentioned above while at the same time crisply capture the flow features. In the present work, an attempt has been made to address the above issues by developing yet another kinetic scheme, known as the low dissipative modified KFVS (m-KFVS) method based on modified CIR (MCIR) splitting with molecular velocity dependent dissipation control function. Different choices for the dissipation control function are presented. A detailed mathematical analysis and the underlying physical arguments behind these choices are presented. The expressions for the m-KFVS fluxes are derived. For one of the choices, the expressions for the split fluxes are similar to the usual first order KFVS method. The mathematical properties of 1D m-KFVS fluxes and the eigenvalues of the corresponding flux Jacobians are studied numerically. The analysis of numerical dissipation is carried out both at Boltzmann and Euler levels. The expression for stability criterion is derived. In order to be consistent with the interior scheme, modified solid wall and outer boundary conditions are derived by extending the MCIR idea to boundaries. The cell-centred finite volume method based on m-KFVS is applied to several standard test cases for 1D, 2D and 3D inviscid flows. In the case of subsonic flows, the m-KFVS method produces much less numerical entropy compared to first order KFVS method and the results are comparable to second order accurate q-KFVS method. In transonic and supersonic flows, m-KFVS generates much less numerical dissipation compared to first order KFVS and even less compared to q-KFVS method. Further, the m-KFVS method captures the discontinuities more sharply with contours being smooth and near second order accuracy has been achieved in smooth regions, by still using first order stencil. Therefore, the numerical dissipation generated by m-KFVS is considerably reduced by suitably choosing the dissipation control variables. The Euler code based on m-KFVS method almost takes the same amount of computational time as that of KFVS method. Although, the formal accuracy is of order one, the m-KFVS method resolves the flow features much more accurately compared to first order KFVS method but the numerical dissipation generated by m-KFVS method may not be minimal. Hence, the dissipation control vector is in general not optimal. If we can find the optimal dissipation control vector then we will be able to achieve the minimal dissipation. In the present work, the above objective is attained by posing the minimisation of numerical dissipation in m-KFVS method as an optimal control problem. Here, the control variables are the dissipation control vector. The discrete form of the cost function, which is to be minimised is considered as the sum of the squares of change in entropy at all cells in the computational domain. The number of control variables is equal to the total number of cells or finite volumes in the computational domain, as each cell has only one dissipation control variable. In the present work, the minimum value of cost function is obtained by using gradient based optimisation method. The sensitivity gradients of the cost function with respect to the control variables are obtained using discrete adjoint approach. The discrete adjoint equations for the optimisation problem of minimising the numerical dissipation in m-KFVS method applied to 2D and 3D Euler equations are derived. The method of steepest descent is used to update the control variables. The automatic differentiation tool Tapenade has been used to ease the development of adjoint codes. The m-KFVS code combined with discrete adjoint code is applied to several standard test cases for inviscid flows. The test cases considered are, low Mach number flows past NACA 0012 airfoil and two element Williams airfoil, transonic and supersonic flows past NACA 0012 airfoil and finally, transonic flow past Onera M6 wing. Numerical results have shown that the m-KFVS-adjoint method produces even less numerical dissipation compared to m-KFVS method and hence results in more accurate solution. The m-KFVS-adjoint code takes more computational time compared to m-KFVS code. The present work demonstrates that it is possible to achieve near second order accuracy by formally first order accurate m-KFVS scheme while retaining advantages of first order accurate methods.

Face aux forts besoins de réduction de la consommation énergétique et de l’impact environnemental,le bâtiment d’aujourd’hui vise la performance en s’appuyant sur des sourcesd’énergie de plus en plus diversifiées (énergies renouvelables), une enveloppe mieux conçue(isolation) et des systèmes de gestion plus avancés. Plus la conception vise la basse consommation,plus les interactions entre ses composants sont complexes et peu intuitives. Seule unerégulation plus intégrée permettrait de prendre en compte cette complexité et d’optimiser lefonctionnement pour atteindre la basse consommation sans sacrifier le confort.Les techniques de commande prédictive, fondées sur l’utilisation de modèles dynamiqueset de techniques d’optimisation, promettent une réduction des consommations et de l’inconfort.Elles permettent en effet d’anticiper l’évolution des sources et des besoins intermittentstout en tirant parti de l’inertie thermique du bâtiment, de ses systèmes et autres élémentsde stockage. Cependant, dans le cas du bâtiment, l’obtention d’un modèle dynamique suffisammentprécis présente des difficultés du fait d’incertitudes importantes sur les paramètresdu modèle et les sollicitations du système. Les avancées récentes dans le domaine de l’instrumentationdomotique constituent une opportunité prometteuse pour la réduction de cesincertitudes, mais la conception d’un tel système pour une telle application n’est pas triviale.De fait, il devient nécessaire de pouvoir considérer les problématiques de monitoring énergétique,d’instrumentation, de commande prédictive et de modélisation de façon conjointe.Cette thèse vise à identifier les liens entre commande prédictive et instrumentation dansle bâtiment, en proposant puis exploitant une méthode générique de modélisation du bâtiment,de simulation thermique et de résolution de problèmes d’optimisation. Cette méthodologiemet en oeuvre une modélisation thermique multizone du bâtiment, et des algorithmesd’optimisation reposant sur un modèle adjoint et les outils du contrôle optimal. Elle a étéconcrétisée dans un outil de calcul permettant de mettre en place une stratégie de commandeprédictive comportant des phases de commande optimale, d’estimation d’état et decalibration.En premier lieu, nous étudions la formulation et la résolution d’un problème de commandeoptimale. Nous abordons les différences entre un tel contrôle et une stratégie de régulationclassique, entre autres sur la prise en compte d’indices de performance et de contraintes. Nousprésentons ensuite une méthode d’estimation d’état basée sur l’identification de gains thermiquesinternes inconnus. Cette méthode d’estimation est couplée au calcul de commandeoptimale pour former une stratégie de commande prédictive.Les valeurs des paramètres d’un modèle de bâtiment sont souvent très incertaines. Lacalibration paramétrique du modèle est incontournable pour réduire les erreurs de prédictionet garantir la performance d’une commande optimale. Nous appliquons alors notreméthodologie à une technique de calibration basée sur des mesures de températures in situ.Nous ouvrons ensuite sur des méthodes permettant d’orienter le choix des capteurs à utiliser(nombre, positionnement) et des paramètres à calibrer en exploitant les gradients calculéspar la méthode adjointe.La stratégie de commande prédictive a été mise en oeuvre sur un bâtiment expérimentalprès de Chambéry. Dans le cadre de cette étude, l’intégralité du bâtiment a été modélisé,et les différentes étapes de notre commande prédictive ont été ensuite déployées de mainière séquentielle. Cette mise en oeuvre permet d’étudier les enjeux et les difficultés liées àl’implémentation d’une commande prédictive sur un bâtiment réel.Cette thèse est issue d’une collaboration entre le CEA Leti, l’IFSTTAR de Nantes et leG2ELab, et s’inscrit dans le cadre du projet ANR PRECCISION. / More efficient energy management of buildings through the use of Model Predictive Control(MPC) techniques is a key issue to reduce the environmental impact of buildings. Buildingenergy performance is currently improved by using renewable energy sources, a betterdesign of the building envelope (insulation) and the use of advanced management systems.The more the design aims for high performance, the more interactions and coupling effectsbetween the building, its environment and the conditions of use are important and unintuitive.Only a more integrated regulation would take in account this complexity, and couldhelp to optimize the consumption without compromising the comfort.Model Predictive Control techniques, based on the use of dynamic models and optimizationmethods, promise a reduction of consumption and discomfort. They can generate energysavings by anticipating the evolution of renewable sources and intermittent needs, while takingadvantage of the building thermal inertia and other storage items. However, in the caseof buildings, obtaining a good dynamic model is tough, due to important uncertainties onmodel parameters and system solicitations.Recent advances in the field of wireless sensor networks are fostering the deployment ofsensors in buildings, and offer a promising opportunity to reduce these errors. Nevertheless,designing a sensor network dedicated to MPC is not obvious, and energy monitoring,instrumentation, modeling and predictive control matters must be considered jointly.This thesis aims at establishing the links between MPC and instrumentation needs inbuildings. We propose a generic method for building modeling, thermal simulation andoptimization. This methodology involves a multi-zone thermal model of the building, andefficient optimization algorithms using an adjoint model and tools from the optimal controltheory. It was implemented in a specific toolbox to develop a predictive control strategywith optimal control phases, state estimation phases and model calibration.At first, we study the formulation and resolution of an optimal control problem. We discussthe differences between such a control and a conventional regulation strategy, throughperformance indicators. Then, we present a state estimation method based on the identificationof unknown internal gains. This estimation method is subsequently coupled with theoptimal control method to form a predictive control strategy.As the parameters values of a building model are often very uncertain, parametric modelcalibration is essential to reduce prediction errors and to ensure the MPC performance. Consequently,we apply our methodology to a calibration technique based on in situ temperaturemeasurements. We also discuss how our approach can lead to selection techniques in orderto choose calibrated parameters and sensors for MPC purposes.Eventually, the predictive control strategy was implemented on an experimental building,at CEA INES, near Chambéry. The entire building was modeled, and the different steps ofthe control strategy were applied sequentially through an online supervisor. This experimentgave us a useful feedback on our methodology on a real case.This thesis is the result of a collaboration between CEA Leti, IFSTTAR Nantes andG2ELab, and is part of the ANR PRECCISION project.

Submitted by Aelson Maciera (aelsoncm@terra.com.br) on 2017-06-27T20:42:50Z No. of bitstreams: 1 DissLFL.pdf: 818058 bytes, checksum: a45e8f4dbdc692c6f31fde1d45f6574d (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-07-03T17:56:46Z (GMT) No. of bitstreams: 1 DissLFL.pdf: 818058 bytes, checksum: a45e8f4dbdc692c6f31fde1d45f6574d (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-07-03T17:56:52Z (GMT) No. of bitstreams: 1 DissLFL.pdf: 818058 bytes, checksum: a45e8f4dbdc692c6f31fde1d45f6574d (MD5) / Made available in DSpace on 2017-07-03T18:01:59Z (GMT). No. of bitstreams: 1 DissLFL.pdf: 818058 bytes, checksum: a45e8f4dbdc692c6f31fde1d45f6574d (MD5) Previous issue date: 2016-12-20 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / In this thesis, we present a priori estimates for solutions of a mean-field game (MFG) defined over a bounded domain Ω ⊂ ℝd. We propose an application of these results to a model of capital and wealth accumulation. In Chapter 1, an introduction to mean-field games is presented. We also put forward some of the motivation from Economics and discuss previous developments in the theory of differential games. These comments aim at indicating the connection between mean-field games theory, its applications and the realm of Mathematical Analysis. In Chapter 2, we present an optimal control problem. Here, the agents are supposed to be undistinguishable, rational and intelligent. Undistinguishable means that every agent is governed by the same stochastic differential equation. Rational means that all efforts of the agent is to maximize a payoff functional. Intelligent means that they are able to solve an optimal control problem. Once we describe this (stochastic) optimal control problem, we produce a heuristic derivation of the mean-field games system, which is summarized in a Verification Theorem; this gives rise to the Hamilton-Jacobi equation (HJ). After that, we obtain the Fokker-Plank equation (FP). Finally, we present a representation formula for the solutions to the (HJ) equation, together with some regularity results. In Chapter 3, a specific optimal control problem is described and the associated MFG is presented. This MFG is prescribed in a bounded domain Ω ⊂ ℝd, which introduces substantialadditional challenges from the mathematical view point. This is due to estimates for the solutionsat the boundary in Lp. The rest of the chapter puts forward two well known tips of estimates: theso-called Hopf-Lax formula and the First Order Estimate. In Chapter 4, the wealth and capital accumulation mean-field game model is presented. The relevance of studying MFG in a bounded domain then becomes clear. In light of the results obtained in Chapter 3, we close Chapter 4 with the Hopf-Lax formula, and the First Order estimates. Three appendices close this thesis. They gather elementary material on Stochastic Calculus and Functional Analysis. / Nesta dissertação são apresentadas algumas estimativas a priori para soluções de sistemas mean-field games (MFG), definidos em domínios limitados Ω ⊂ ℝd. Tais estimativas são aplicadas em um modelo mean-field específico, que descreve o acúmulo de riqueza e capital. No Capítulo 1, é apresentada uma breve introdução histórica sobre os mean-field games. Nesta introdução, exploramos sua relação com a teoria dos jogos, cujos alicerces foram construídos por economistas e matemáticos ao longo do século XX. O objetivo do capítulo é transmitir. No Capítulo 2, apresentamos um problema de controle ótimo em que cada agente é suposto ser indistinguível, racional e inteligente. Indistinguível no sentido de que cada um é governado pela mesma equação diferencial estocástica. Racional no sentido de que todos os esforços do agente são no sentido de maximizar um funcional de recompensa e, inteligente no sentido de que são capazes de resolver um problema de controle ótimo. Descreve-se este problema de controle ótimo, e apresenta-se a derivação heurística dos mean-field games; obtém-se através de um Teorema de Verificação, a equação de Hamilton-Jacobi (HJ) associada, e em seguida, obtémse a equação de Fokker-Planck. De posse destas equações, apresentamos alguns resultados preliminares, como uma fórmula de representação para soluções da equação de HJ e alguns resultados de regularidade. No Capítulo 3, descreve-se um problema específico de controle ótimo e apresenta-se a respectiva derivação heurística culminando na descrição de um MFG com condições não periódicas na fronteira; esta abordagem é original na literatura de MFG. O restante do capítulo é dedicado à exposição de dois tipos bem conhecidos de estimativas: a fórmula de Hopf-Lax e estimativa de Primeira Ordem. Uma observação relevante, é a de que o trabalho em obter-se estimativas a priori é aumentado substancialmente neste caso, devido ao fato de lidarmos com estimativas para os termos de fronteira com normas em Lp. ao leitor, as origens da Teoria Econômica contemporânea, que surgem à partir da utilização da Matemática na formulação e resolução de problemas econômicos. Tal abordagem é motivada principalmente pelo rigor e clareza da Matemática em tais circunstâncias. No Capítulo 4, apresenta-se o modelo de jogo do tipo mean-field de acúmulo de capital e riqueza, o que deixa claro a relevância do estudo dos MFG em um domínio limitado. À luz dos resultados obtidos no Capítulo 3, encerramos o Capítulo 4 com as estimativas do tipo Hopf-Lax e de Primeira Ordem. Três apêndices encerram o texto desta dissertação de mestrado; estes reúnem material elementar sobre Cálculo Estocástico e Análise Funcional.

Originally developed in the 1970s for the optimal control of systems governed by partial differential equations, the adjoint method has found several successful applications, e.g. in meteorology with large-scale 3D or 4D atmospheric data assimilation schemes, for carbon cycle data assimilation in biogeochemistry and climate research, or in oceanographic modelling with efficient adjoint codes of ocean general circulation models.<p><p>Despite the variety of applications in these research fields, adjoint methods have only very recently drawn attention from the ocean acoustics community. In ocean acoustic tomography and geoacoustic inversion, where the inverse problem is to recover unknown acoustic properties of the water column and the seabed from acoustic transmission data, the solution approaches are typically based on travel time inversion or standard matched-field processing in combination with metaheuristics for global optimization. <p><p>In order to complement the adjoint schemes already in use in meteorology and oceanography with an ocean acoustic component, this thesis is concerned with the development of the adjoint of a full-field acoustic propagation model for shallow water environments. <p><p>In view of the increasing importance of global ocean observing systems such as the European Seas Observatory Network, the Arctic Ocean Observing System and Maritime Rapid Environmental Assessment (MREA) systems for defence and security applications, the adjoint of an ocean acoustic propagation model can become an integral part of a coupled oceanographic and acoustic data assimilation scheme in the future. <p><p>Given the acoustic pressure field measured on a vertical hydrophone array and a modelled replica field that is calculated for a specific parametrization of the environment, the developed adjoint model backpropagates the mismatch (residual) between the measured and predicted field from the receiver array towards the source.<p><p>The backpropagated error field is then converted into an estimate of the exact gradient of the objective function with respect to any of the relevant physical parameters of the environment including the sound speed structure in the water column and densities, compressional/shear sound speeds, and attenuations of the sediment layers and the sub-bottom halfspace. The resulting environmental gradients can be used in combination with gradient descent methods such as conjugate gradient, or Newton-type optimization methods tolocate the error surface minimum via a series of iterations. This is particularly attractive for monitoring slowly varying environments, where the gradient information can be used to track the environmental parameters continuously over time and space.<p><p>In shallow water environments, where an accurate treatment of the acoustic interaction with the bottom is of outmost importance for a correct prediction of the sound field, and field data are often recorded on non-fully populated arrays, there is an inherent need for observation over a broad range of frequencies. For this purpose, the adjoint-based approach is generalized for a joint optimization across multiple frequencies and special attention is devoted to regularization methods that incorporate additional information about the desired solution in order to stabilize the optimization process.<p><p>Starting with an analytical formulation of the multiple-frequency adjoint approach for parabolic-type approximations, the adjoint method is progressively tailored in the course of the thesis towards a realistic wide-angle parabolic equation propagation model and the treatment of fully nonlocal impedance boundary conditions. A semi-automatic adjoint generation via modular graph approach enables the direct inversion of both the geoacoustic parameters embedded in the discrete nonlocal boundary condition and the acoustic properties of the water column. Several case studies based on environmental data obtained in Mediterranean shallow waters are used in the thesis to assess the capabilities of adjoint-based acoustic inversion for different experimental configurations, particularly taking into account sparse array geometries and partial depth coverage of the water column. The numerical implementation of the approach is found to be robust, provided that the initial guesses are not too far from the desired solution, and accurate, and converges in a small number of iterations. During the multi-frequency optimization process, the evolution of the control parameters displays a parameter hierarchy which clearly relates to the relative sensitivity of the acoustic pressure field to the physical parameters. <p><p>The actual validation of the adjoint-generated environmental gradients for acoustic monitoring of a shallow water environment is based on acoustic and oceanographic data from the Yellow Shark '94 and the MREA '07 sea trials, conducted in the Tyrrhenian Sea, south of the island of Elba.<p> <p>Starting from an initial guess of the environmental control parameters, either obtained through acoustic inversion with global search or supported by archival in-situ data, the adjoint method provides an efficient means to adjust local changes with a couple of iterations and monitor the environmental properties over a series of inversions. <p><p>In this thesis the adjoint-based approach is used, e.g. to fine-tune up to eight bottom geoacoustic parameters of a shallow-water environment and to track the time-varying sound speed profile in the water column. <p><p>In the same way the approach can be extended to track the spatial water column and bottom structure using a mobile network of sparse arrays.<p><p>Work is currently being focused on the inclusion of the adjoint approach into hybrid optimization schemes or ensemble predictions, as an essential building block in a combined ocean acoustic data assimilation framework and the subsequent validation of the acoustic monitoring capabilities with long-term experimental data in shallow water environments. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

L’adaptation de maillage est un outil puissant pour l’obtention de simulations aérodynamiques précises à coût limité. Dans le cas particulier des simulations visant au calcul de fonctions aérodynamiques (efforts, moments, rendements...), plusieurs méthodes dites de raffinement ciblé (ou, en anglais, « goal-oriented ») basées sur le vecteur adjoint de la fonction d’intérêt ont été proposées. L’objectif de la thèse est l’extension d’une méthode de ce type basée sur la dérivée totale dJ/dX de la grandeur aérodynamique d’intérêt, J, par rapport aux coordonnées du maillage volumique, X. Les trois méthodes usuelles de calcul de gradient discret – la méthode de différentiation directe, la méthode adjointe-"paramètres" et la méthode adjointe-"maillage" évaluant dJ/dX – ont tout d’abord été étudiées et codées dans le logiciel elsA de l’ONERA pour des maillages non-structurés, pour des écoulements compressibles de fluide parfait et des écoulements laminaires. La seconde étape du travail a consisté à créer un senseur local θ basé sur dJ/dX qui identifie les zones du maillage volumique où la position des nœuds a une forte incidence sur l’évaluation de la fonction J. Ce senseur sert d’indicateur pour l’adaptation de différents maillages, pour différents régimes d’écoulement (subsonique, transsonique, supersonique), pour des configurations d’aérodynamique interne (aube et tuyère) et externe (profil d’aile). La méthode proposée est comparée à une méthode de raffinement ciblée très populaire (Venditti et Darmofal, 2001) et à une méthode de raffinement basée sur les caractéristiques de l’écoulement (ou, en anglais, « feature-based ») ; elle conduit à des résultats très satisfaisants. / Mesh adaptation is a powerful tool to obtain accurate aerodynamic simulations with limited cost. In the specific case of computation of aerodynamic functions (forces, moments, efficiency ...), goal-oriented methods based on the adjoint vector have been proposed. The aim of the thesis is the extension of a method of this type based on the total derivative dJ/dX of the aerodynamic output of interest, J, with respect to the volume mesh coordinates, X. The three common methods for calculating discrete gradient – the direct differentiation method, the parameter-adjoint method and mesh-adjoint method evaluating dJ/dX – have been studied first and coded in the elsA ONERA software for unstructured grids, for compressible inviscid and laminar flows. The second part of this work was has been to define a local sensor θ based on dJ/dX in order to identify zones where the volume mesh nodes position has a strong impact on the evaluation of the function J. This sensor is the selected indicator for different mesh adaptations for different flow regimes (subsonic, transonic, supersonic) for internal (blade and nozzle) and external (wing profile) aerodynamic configurations. The proposed method is compared to a well-known goal-oriented method (Darmofal and Venditti, 2001) and to a feature-based method ; it leads to very consistent results. very consistent results.