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Academic literature on the topic 'Décomposition généralisée propre'
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Journal articles on the topic "Décomposition généralisée propre"
Pang, C. Y. Amy. "Card-Shuffling via Convolutions of Projections on Combinatorial Hopf Algebras." Discrete Mathematics & Theoretical Computer Science DMTCS Proceedings, 27th..., Proceedings (January 1, 2015). http://dx.doi.org/10.46298/dmtcs.2511.
Full textBouvier, Pierre. "Socioanthropologie." Anthropen, 2016. http://dx.doi.org/10.17184/eac.anthropen.026.
Full textDissertations / Theses on the topic "Décomposition généralisée propre"
Nguyen, Tuan Linh. "La Décomposition propre généralisée pour la résolution de problèmes multiphysiques transitoires couplés dédiés à la mécanique des matériaux." Chasseneuil-du-Poitou, Ecole nationale supérieure de mécanique et d'aérotechnique, 2012. https://theses.hal.science/docs/00/78/59/85/PDF/manuscrit_final_NGUYEN_Tuan_Linh_ENSMA_Poitiers_v2B.pdf.
Full textThis work presents the development of the Proper Generalized Decomposition (PGD) method for solving couple transient multiphysics problems with different characteristic times. This method consists in approximating solutions ( Partial Differentiai Equations with separated representations. The 2D transient heat equation is initially considered. A automatic adaptive mesh technique is proposed in order to make the discretization fit the different transient domains. Tw different couplings between the PGD method and the adaptive mesh refinement technique are discussed: the frrst on consists in computing the PGD solution for each new mesh from the null solution; the second one consists in enrichin the PGD solution for each new mesh from the basis functions generated on the previous meshes. The frrst coupling. More efficient since fewer modes are required to accurately describe the solution on the final mesh. Nevertheless, th second one decreases the number of enrichments cumulated tbrough the mesh refmement pro cess. Regardless of th coupling used, the adaptive mesh technique is able to automatically describe the localized transient zones. The II transient heat equation with a non linear source term is also studied. A new approach combining the PGD method and th Asymptotic Numerical Method (ANM) is tested, which allows to efficiently solve sorne families of non linear transiel problems. Finally, two muItitime and multiphysics problems are considered. It consists of a partially coupled he diffusion problem and a strongly coupled thermoviscoelastic problem. The PGD method gives an accurate prediction c the response of these muItiphysics problems for which the coupling terms lead to specific transient zones. Combined wit the PGD method, the adaptive mesh technique is particularly suitable for these situations of strongly coupled tim multiscale. This combination brings to the same conclusions as in the case of a single physical phenomenon. The discussion focuses on two strategies of mesh construction: concatenating the time meshes of each physical phenomeno or refme each mesh independently. The concatenation of two meshes allows a convergence with fewer steps of mes refmement but with a much bigher mesh density
Qin, Zhi. "Finite element modelling and PGD based model reduction for piezoelectric and magnetostrictive materials." Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066566/document.
Full textThe energy harvesting technology that aims to enable wireless sensor networks (WSN) to be maintenance-free, is recognized as a crucial part for the next generation technology mega- trend: the Internet of Things (IoT). Piezoelectric and magnetostrictive materials, which can be used in a wide range of energy harvesting systems, have attracted more and more interests during the past few years. This thesis focuses on multiphysics finite element (FE) modeling of these two materials and performing model reduction for resultant systems, based on the Prop- er Generalized Decomposition (PGD). Modeling these materials remains challenging although research in this area has been under- going over decades. A multitude of difficulties exist, among which the following three issues are largely recognized. First, mathematically describing properties of these materials is com- plicated, which is particularly true for magnetostrictive materials because their properties depend on factors including temperature, stress and magnetic field. Second, coupling effects between electromagnetic, elastic, and thermal fields need to be considered, which is beyond the capability of most existing simulation tools. Third, as systems becoming highly integrated whole-scale simulations become necessary, which means three dimensional (3D) numerical models should be employed. 3D models, on the other hand, quickly turns intractable if not properly built. The work presented here provides solutions in respond to the above challenges. A differential forms based multiphysics FE framework is first established. Within this frame- work quantities are discreted using appropriate Whitney elements. After discretization, the system is solved as a single block, thus avoiding iterations between different physics solutions and leading to rapid convergences. Next, the linear piezoelectric, and a free energy based nonlinear magnetostrictive constitutive model called Discrete Energy Averaged Model (DE- AM) are incorporated into the framework. Our implementation describes underlying material behaviors at reasonable numerical costs. Eventually, two novel PGD based algorithms for model reduction are proposed. With our algorithms, problem size of multiphysics models can be significantly reduced while final results of very good accuracy are obtained. Our algo- rithms also provide means to handle coupling and nonlinearity conveniently. All our methodologies are demonstrated and verified via representative examples
Oulghelou, Mourad. "Développement de modèles réduits adaptatifs pour le contrôle optimal des écoulements." Thesis, La Rochelle, 2018. http://www.theses.fr/2018LAROS014/document.
Full textThe numerical resolution of adjoint based optimal control problems requires high computational time and storage capacities. In order to get over these high requirement, it is possible to use model reduction techniques such as POD (Proper Orthogonal Decomposition). The disadvantage of this approach is that the POD basis is valid only for parameters located in a small neighborhood to the parameters for which it was built. Therefore, this basis may not be representative for all parameters in the optimizer’s path eventually suggested by the optimal control loop. To overcome this issue, a reduced optimal control methodology using adaptive reduced order models obtained by the ITSGM (Interpolation on a Tangent Subspace of the Grassman Manifold) method or by the PGD (Proper Generalized Decomposition) method, has been proposed in this work. The robustness of this approach in terms of precision and computation time has been demonstrated for the optimal control (based on adjoint equations) of the 2D reaction-diffusion and Burgers equations. The interpolation method ITSGM has also been validated in the control of flow around a 2D cylinder. In the context of non intrusive model reduction, two non intrusive reduction methods, which do not require knowledge of the equations of the studied model, have also been proposed. These methods called NIMR (Non-Intrusive Model Reduction) and HNIMR (Hyper Non-Intrusive Model Reduction) were developed and then coupled to a genetic algorithm in order to solve an optimal control problem in quasi-real time. The problem of optimal control of the flow around a 2D cylinder has been studied and the results have shown the effectiveness of this approach. Indeed, the genetic algorithm coupled with the HNIMR method allowed to obtain the solutions with a good accuracy in less than 40 seconds
Saleh, Marwan. "Étude mathématique et numérique des méthodes de réduction dimensionnelle de type POD et PGD." Thesis, La Rochelle, 2015. http://www.theses.fr/2015LAROS004/document.
Full textThis thesis is formed of four chapters. The first one presents the mathematical notions and tools used in this thesis and gives a description of the main results obtained within. The second chapter presents our generalization of a result obtained by Rousselet-Chenais in 1990 which describes the sensitivity of eigensubspaces for self-adjoint compact operators. Rousselet-Chenais were limited to sensitivity for specific subspaces of dimension 1, we have extended their result to higher dimensions. We applied our results to the Proper Orthogonal Decomposition (POD) in the case of parametric, temporal and spatial variations (Gappy- POD). The third chapter discusses the optical flow estimate with quadratic or linear energies at infinity. Mathematical results of convergence are shown for the method Progressive Generalized Decomposition (PGD) in the case of quadratic energies. Our proof is based on the decomposition of Brézis-lieb via the convergence almost everywhere of the PGD sequence gradients. A detailed numerical study is made on different types of images : on the passive scalar transport equations, whose displacement fields are solutions of the Navier-Stokes equations. These equations present a challenge for optical flow estimates because of the presence of low gradient regions in the image. We applied our method to the MRI image sequences to estimate the movement of the abdominal organs. PGD presented a superiority in both computing time level (even in 2D) and accuracy representation of the estimated motion. The local diffusion of standard methods (Horn Schunck, for example) limits the convergence rate, in contrast to the PGD which is a more global approach by construction. The last chapter deals with the application of PGD method in the case of variational elliptic equations whose energy present all challenges to classical variational methods : lack of convexity, lack of coercivity and lack of boundedness. We prove convergence results for the weak topology, the PGD sequences converge (when they are well defined) to two extremal solutions on the Nehari manifold. Several mathematical questions about PGD remain open in this chapter. These questions are part of our research perspectives
Metoui, Sondes. "Separated représentations for th multiscale simulation of the mechanical behavior and damages of composite materials." Thesis, Paris, ENSAM, 2015. http://www.theses.fr/2015ENAM0049/document.
Full textSeparated representations for the multiscale simulation of the mechanicalbehavior and damages of composite materials.Abstract: The development of efficient simulations for composite structures is very challengingdue to the multiscale nature and the complex damage process of this materials. When usingstandard 3D discretization techniques with advanced models for large structures, the computationalcosts are generally prohibitive.In this thesis, a new strategy based on a separated represenation of the solution is explored todevelop a computationally efficient and reliable numerical framework for the analysis of damagesin laminated composites subjected to quasi-static and dynamic loading. The PGD (Proper GeneralizedDecomposition) is used to build the solution.To treat damage, and especially delamination, a cohesive zone model has been implemented inthe PGD solver. A novel multiscale approach is also proposed to compute the mechanical behaviorof composites with periodic microstructure. The idea is to separate two scales: the scaleof periodic pattern and the macroscopic scale. The PGD results have been compared with theresults obtained with the classcial finite element method. A close agreement is found between thetwo approach and the PGD has significantly reduced the model complexity
Maitrejean, Guillaume. "Couplages moléculaire- théorie cinétique pour la simulation du comportement des matériaux complexes." Thesis, Grenoble, 2011. http://www.theses.fr/2011GRENI067/document.
Full textThis work is a contribution to the numerical modeling of suspension system in the kinetic theory framework. This continuum description of suspension system allows to account for the microstructure impact on the kinetic of the macroscopic flow. However, its main drawback is related to the high dimensional spaces in which kinetic theory models are defined and makes difficult for classical deterministic approaches to solve such systems. One possibility for circumventing, or at least alleviate, the weight of the micro-macro kinetic theory approaches lies in the use of separated representations strategies based on the Proper Generalized Decomposition (PGD). A study of different PGD algorithms is driven, illustrating the efficiency of these algorithms in terms of convergence speed and optimality of the solution obtained. The immiscible fluids blends modeling is driven using the area tensor which is a powerful numerical tool for characterizing blends. However it needs the introduction of closure relation of which impact is measured using equivalent and exact kinetic theory model. Finally, the numerical modeling of colloidal suspension system described by the Smoluchowski equation presents an original approach of the modeling of solid suspension system. This description allows to circumvent the statistical noise inherent to the stochastic approaches commonly used
Paillet, Charles. "Nouvelles démarches de réduction de modèles pour le traitement des problèmes à très grand nombre de paramètres." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLN015/document.
Full textNumerical simulation is nowadays a major tool in a large number of engineering fields. Nevertheless, even the recent incredible improvements of the computational power can hardly compensate the increasing complexity of the models used by engineers. In this context, Reduced Order Models (ROM) can be major decision-maker tools because, once they have been computed, they can be used to evaluate a very large number of test cases in a duration close to real time. The PGD (Proper Generalized Decomposition) in particular, is a method introduced at the LMT which has been adapted to many cases (non-linear problems, multiscale, multiphysics) and leads to savings of CPU time reaching several orders of magnitude.Unfortunately, it is currently difficult to build ROM with an increasing number of parameters. All the actual model reduction technics (including the PGD) can hardly solve problems with a high number of parameters (the current limit is about twenty parameters). It is a major barrier to a larger development of these methods. This PhD thesis presents a new methodology based on the PGD able to take into account high numbers of parameters.This goal has been achived thanks to three major contributions. First, a new data structure faithfull to mecanical properties of the problem has been developed. To that end, two different scales are introduced in the parametric space, giving its name to our method : Parameter-Multiscale PGD. Furthermore, the WTDG (Weak Treffz Discontinuous Galerkin) method has been inpemented. It is a discontinuous spatial discretisation adapted to our resolution techniques. Finally, new algorithms have been developed to built reduced order models of problems taking into account up to one thousand parameters
Al, Takash Ahmad. "Development of Numerical Methods to Accelerate the Prediction of the Behavior of Multiphysics under Cyclic Loading." Thesis, Chasseneuil-du-Poitou, Ecole nationale supérieure de mécanique et d'aérotechnique, 2018. http://www.theses.fr/2018ESMA0014/document.
Full textIn the framework of structural calculation, the reduction of computation time plays an important rolein the proposition of failure criteria in the aeronautic and automobile domains. Particularly, the prediction of the stabilized cycle of polymer under cyclic loading requires solving of a thermo-viscoelastic problem with a high number of cycles. The presence of different time scales, such as relaxation time (viscosity), thermal characteristic time (thermal), and the cycle time (loading) lead to a huge computation time when an incremental scheme is used such as with the Finite Element Method (FEM).In addition, an allocation of memory will be used for data storage. The objective of this thesis isto propose new techniques and to extend existent ones. A transient thermal problem with different time scales is considered in the aim of computation time reduction. The proposed methods are called model reduction methods. First, the Proper Generalized Decomposition method (PGD) was extended to a nonlinear transient cyclic 3D problems. The non-linearity was considered by combining the PGD method with the Discrete Empirical Interpolation Method (DEIM), a numerical strategy used in the literature. Results showed the efficiency of the PGD in generating accurate results compared to the FEM solution with a relative error less than 1%. Then, a second approach was developed in order to reduce the computation time. It was based on the collection of the significant modes calculated from the PGD method for different time scales. A dictionary assembling these modes is then used to calculate the solution for different characteristic times and different boundary conditions. This approach was adapted in the case of a weak coupled diffusion thermal problem. The novelty of this method is to consider a dictionary composed of spatio-temporal bases and not spatial only as usedin the POD. The results showed again an exact reproduction of the solution in addition to a huge time reduction. However, when different cycle times are considered, the number of modes increases which limits the usage of the approach. To overcome this limitation, a third numerical strategy is proposed in this thesis. It consists in considering a priori known time bases and is called the mixed strategy. The originality in this approach lies in the construction of a priori time basis based on the Fourier analysis of different simulations for different time scales and different values of parameters.Once this study is done, an analytical expression of time bases based on parameters such as the characteristic time and the cycle time is proposed. The related spatial bases are calculated using the PGD algorithm. This method is then tested for the resolution of 3D thermal problems under cyclic loading linear and nonlinear and a weak coupled diffusion thermal problem
Sandino, de Benito Carlos. "Global-local separated representations based on the Proper Generalized Decomposition." Thesis, Ecole centrale de Nantes, 2019. http://www.theses.fr/2019ECDN0064.
Full textOne of the main advantages of the Proper Generalized Decomposition method, when compared to other model reduction methods, lies in its adequacy to compute space separated representations in Cartesian-like degenerated domains, such as plates or shells. The main objective of this thesis is to generalize space separated representations to non-Cartesian domains, by introducing the notion of Global-Local separated representations. Global-Local separated representations can be understood as a multiplicative decomposition in which the local modes capture the solution at the finer scale, while the global modes solve the coarser scale. To this aim, two strategies are proposed. The first proposal is based on the partition of unity, and combines the global and local discretization levels, based on a partition of the domain. It builds a separated representation that provides the local enrichment, without the need for a priori knowledge of the solution, nor the implementation of auxiliary local problems to determine the enrichment. The second strategy is devoted to the construction of Global-Local separated representations in a less intrusive manner, compatible with the finite element standard. Therefore, we rely on standard FEM assembly of the operators and use the PGD as an algebraic iterative solver. Continuity on the boundaries of the domain’s partition does not need to be imposed explicitly, as it comes as a built-in property of the FEM operators
Maitrejean, Guillaume. "Contributions à la modélisation numérique de la théorie cinétique des suspensions." Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00681032.
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