Dissertations / Theses on the topic 'Sous-espaces de Krylov, Méthode des'
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Elbouyahyaoui, Lakhdar. "Etude de quelques méthodes de sous-espaces de Krylov par blocs." Littoral, 2009. http://www.theses.fr/2009DUNK0254.
Full textIn this thesis we study Krylov subspaces methods to solve large scale hollow linear systems. Particularly, we are interested in GMRES method for the standard as well as the blocs case. This method uses Arnoldi process to generate an orthonormal base of Krylov subspaces and introduces a set of new algebraic properties while searching for the solution of the studied system. First of all, we have considered the case of the standard GMRES method, we have explaines the residuals rk and the vectors vk of the base generated by Arnoldi process in the form of polynomials A for r0. By using the classical properties of linear algebra ans Schur complements, we gave new results characterizing the roots of these polynomials witch depends on the eigenvalues of Hessenberg matrices. Algorithms are also presented to calculate these polynomials as well as the minimal polynomials. In the second part, we are interested in the blocs case. We have given the recursive expressions checked by the residuals Rk obtained by the block GMRES method, what enabled us to calculate and to analyze the associated residual polynomials. Thus, by using consecutively the determinant concept and Schur complements we have stated several properties concerning the matrices and the residual polynomials. With this properties, we have evoked the problem of the research of the values and clean vectors, then we have established new results characterizing the set of clean vectors obtained either by the standard methods or the block methods per. Our interest were particularly about the simplest case, where the matrix A is diagonalisable, we have demonstrated that the block methods present the advantage of better adaptation with the case of the research of the multiple clean vectors. Numerically, we have proposed new implementation of the block GMRES method for solving linear system with multiple right hand sides. This implementation use the block Arnoldi process and the particular structure of the upper block Hessenberg matrix for the minimization of the residual norm and this, without using QR decomposition of the matrix
Hached, Mustapha. "Méthodes de sous-espaces de Krylov matriciels appliquées aux équations aux dérivées partielles." Phd thesis, Université du Littoral Côte d'Opale, 2012. http://tel.archives-ouvertes.fr/tel-00919796.
Full textAbidi, Oussama. "Méthodes de sous-espaces de Krylov rationnelles pour le contrôle et la réduction de modèles." Thesis, Littoral, 2016. http://www.theses.fr/2016DUNK0419/document.
Full textMany physical phenomena are modeled by PDEs. The discretization of these equations often leads to dynamical systems (continuous or discrete) depending on a control vector whose choice can stabilize the dynamical system. As these problems are, in practice, of a large size, it is interesting to study the problem through another one which is reduced and close to the original model. In this thesis, we develop and study new methods based on rational Krylov-based processes for model reduction techniques in large-scale Multi-Input Multi-Output (MIMO) linear time invariant dynamical systems. In chapter 2 the methods are based on the rational block Arnoldi process to reduce the size of a dynamical system through its transfer function. We provide an adaptive selection choice of shifts that are crucial for the effectiveness of the method. We also introduce a new adaptive Arnoldi-like rational block algorithm to provide a new type of Arnoldi's relationship. In Chapter 3, we develop the new rational global Arnoldi method which is considered as an alternative to the rational block Arnoldi process. We define the projection in the global sense, and apply this method to extract reduced order models that are close to the large original ones. Some new properties and applications are also presented. In chapter 4 of this thesis, we consider the extended block and global Arnoldi methods. We give some new algebraic properties and use them for approaching the firt moments and Markov parameters in moment matching methods for model reduction techniques. In chapter 5, we consider the method of balanced truncation for model reduction. This process is based on the soluytions of two major algebraic equations : Lyapunov equations when the system is stable or Riccati equations when the system is unstable. Since these equations are of large sizes, we will apply the rational block Arnoldi method for solving these equations. In chapter 6, we introduce a new method based on a new subspace called the extended-rational Krylov subspace. We introduce the extended-rational Krylov method which will be used for model reduction in large-scale dynamical systems
Badahmane, Achraf. "Méthodes de sous espaces de Krylov préconditionnées pour les problèmes de point-selle avec plusieurs seconds membres." Thesis, Littoral, 2019. http://www.theses.fr/2019DUNK0543.
Full textIn these last years there has been a surge of interest in saddle point problems. For example, the mechanics of fluids and solids often lead to saddle point problems. These problems are usually presented by partial differential equations that we linearize and discretize. The linear problem obtained is often ill-conditioned. Solving it by standard iterative methods is not appropriate. In addition, when the size of the problem is large, it is necessary to use the projection methods. We are interested in this thesis topic to develop an efficient numerical methods for solving saddle point problems. We apply the Krylov subspace methods incorporated with suitable preconditioners for solving these types of problems. The effectiveness of these methods is illustrated by the numerical experiments
Kaouane, Yassine. "Méthodes tangentielles pour les réductions de modèles et applications." Thesis, Littoral, 2018. http://www.theses.fr/2018DUNK0501/document.
Full textLarge-scale simulations play a crucial role in the study of a great variety of complex physical phenomena, leading often to overwhelming demands on computational resources. Managing these demands constitutes the main motivation for model reduction : produce simpler reduced-order models, which allow for faster and cheaper simulation while accurately approximating the behaviour of the original model. The presence of multiple inputs and outputs (MIMO) systems, makes the reduction process even more challenging. In this thesis we are interested in methods of reducing large-scale models, using projection on tangential Krylov subspaces. We are looking at the development of techniques using tangential interpolation. These present an effective and interesting alternative to the balanced truncation which is considered as a reference in the field and especially for the reduction of linear time invariant systems. Finally, special attention will be focused on the development of new efficient algorithms and application to practical problems
Chen, Langshi. "Méthode de Krylov itératives avec communication et efficacité énergétique optimisées sur machine hétérogène." Thesis, Lille 1, 2015. http://www.theses.fr/2015LIL10114/document.
Full textIterative methods are frequently used in extremely large scale linear problems, such solving linear systems or finding eigenvalue/eigenvectors of matrices. As these iterative methods require a substantial computational workload, they are normally deployed on large clusters of distributed memory architectures communicated via MPI. When the problem size scales up, the communication becomes a major bottleneck of reaching a higher scalability because of two reasons: 1) Many of the iterative methods rely on BLAS-2 low level matrix vector kernels that are communication intensive. 2) Data movement (memory access, MPI communication) is much slower than processor's speed. In case of sparse matrix operations such as Sparse Matrix Vector Multiplication (SpMV), the communication even replaces the computation as the dominant time cost. Furthermore, the advent of accelerators/coprocessors like Nvidia's GPU make computation cost more cheaper, while the communication cost remains high in such CPU-coprocessor heterogeneous systems. Thus, the first part of our work focus on the optimization of communication cost of iterative methods on heterogeneous clusters. Besides the communication cost, power wall becomes another bottleneck of future exascale computing in recent time. Researches indicate that a power-aware algorithmic implementation strategy could efficiently reduce the power dissipation of large clusters. We also explore the potential energy saving implementation of iterative methods in our experimentation. Finally, both the communication optimization and energy efficiency implementation would be integrated into a GMRES method, which demands an auto-tuning framework to maximize its performance
Moufawad, Sophie. "Enlarged Krylov Subspace Methods and Preconditioners for Avoiding Communication." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066438/document.
Full textThe performance of an algorithm on any architecture is dependent on the processing unit’s speed for performing floating point operations (flops) and the speed of accessing memory and disk. As the cost of communication is much higher than arithmetic operations, and since this gap is expected to continue to increase exponentially, communication is often the bottleneck in numerical algorithms. In a quest to address the communication problem, recent research has focused on communication avoiding Krylov subspace methods based on the so called s-step methods. However there are very few communication avoiding preconditioners, and this represents a serious limitation of these methods. In this thesis, we present a communication avoiding ILU0 preconditioner for solving large systems of linear equations (Ax=b) by using iterative Krylov subspace methods. Our preconditioner allows to perform s iterations of the iterative method with no communication, by applying a heuristic alternating min-max layers reordering to the input matrix A, and through ghosting some of the input data and performing redundant computation. We also introduce a new approach for reducing communication in the Krylov subspace methods, that consists of enlarging the Krylov subspace by a maximum of t vectors per iteration, based on the domain decomposition of the graph of A. The enlarged Krylov projection subspace methods lead to faster convergence in terms of iterations and to parallelizable algorithms with less communication, with respect to Krylov methods. We discuss two new versions of Conjugate Gradient, multiple search direction with orthogonalization CG (MSDO-CG) and long recurrence enlarged CG (LRE-CG)
Chagneau, Anthony. "Méthode de zoom structural étendue aux hétérogénéités non linéaires." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTS051.
Full textA multi-scale approach introduces a structural zoom method into a region of interest, called the patch, using only field projection operators. The different behaviours in the patch and in the overall structure are taken into account without using weight parameters between local and global energies such as the Arlequin method. Our initial problem is to digitally reliable the structural zoom method for the linear case, and more precisely to choose a high-performance solver on Krylov spaces, as well as effective preconditioning and ordering adapted to the system to be solved. Once the solver is chosen, this approach is mechanically validated in the mean of two tests, namely traction and shear. A parametric study of the patch is performed to obtain an acceptable solution. The next objective is to extend this approach to regions with heterogeneities of non-linear behaviour. The method has been reached out for elastoplastic behaviour. Initial hypothesis assumes the elastoplastic behaviour only inside the patch and an elastic behaviour of the overall structure as well as of the gluing area. Finally, this approach is validated with different tests including several faults and therefore several patches as well as different loading history
Riquet, Alain-Jérôme. "Méthodes de Krylov par blocs pour les équations matricielles en théorie du contrôle." Littoral, 2002. http://www.theses.fr/2002DUNK0076.
Full textIn this thesis, we explore some methods for solving large numerical problems. These techniques are based on projection processes onto subspaces. We study different projection methods on block krylov subspaces for some large matrix equations. In the first chapter, we propose block Krylov subspace methods for solving Sylvester matrix equations. The proposed methods are based on block Arnoldi, block GMRES and nonsymmetric block Lanczos algorithms. We give some theorical results and numerical experiments to compare the performance of the different methods. In a second chapter, we propose a new Krylov subspace method for solving large Lyapunov matrix equations. The proposed methods are based on the Global-Arnoldi process. We give a new expression of the solution and show how to extract low rank approximate solutions to the Lyapunov matrix equation. We detail also some theorical results. We show how the Krylov subspaces techniques considered above can be applied to the discrete-time Lyapunov equation. We give the Stein-Arnoldi algorithm is a restarted mode. In the third chapter, we give a new block Krylov subspace method to a longe dynamical system by a reduced-order one. The theorical properties of this method are investigated, and a new expression of the Frobenius norm of the approximate residu is derived. We consider an implicity restarted method that can be used to accelerate the convergence speed. We also give experimental results. In the fourth chapter, we describe an algorithm based on the block Lanczos procedure for computing some eigenvalues. We present comparaisons between block Arnoldi and Lanczos procedures for computing eigenvalues of large matrices. We propose the block Chebyshev-Lanczos method for solving nonsymmetric eigenvalues problems. The behavior of this algorithm is illustrated by numerical examples
Paxion, Sébastien. "Développement d'un solveur multigrille non-structuré parallèle pour la simulation de flammes laminaires en chimie et transport complexes." Châtenay-Malabry, Ecole centrale de Paris, 1999. http://www.theses.fr/1999ECAP0681.
Full textHélart, Thomas. "Sur l’optimalité de l’inégalité de Bernstein-Walsh à poids et ses applications aux méthodes de Krylov." Thesis, Lille 1, 2018. http://www.theses.fr/2018LIL1I040/document.
Full textProjection methods on Krylov spaces were used with great success for various tasks in scientific computing, for example the resolution of large systems of linear equations, the approximate computation of eigenvalues, or the approximate computation of matrix functions times a vector. The main goal in this thesis is to study and explain superlinear convergence of Krylov methods. Most of the existing formulas provide asymptotic results for the n-th root considering an increasing sequence of matrices. Firstly, we generalize a formula of Ipsen et al. concerning superlinear convergence of MR methods valid for disks using Hankel operators and AAK theory, our analysis also allows to obtain upper bounds for convex sets using the Faber transform. Then we state our main theorem which is a sharpness result in logarithmic potential theory using a new technique of discretization of a logarithmic potential. We prove that the weighted Bernstein-Walsh inequality on a real interval is sharp up to some universal constant, when the external field is given by a potential of a real measure supported at the left of the interval. As a special case this result includes the case of weights given by polynomials. Via a link with a constrained extremal problem our inequality applies to the analysis of the convergence of Krylov methods, and allows us to predict analytically the superlinear convergence of the conjugate gradient method and of the error for Rayleigh-Ritz approximations for Markov functions. Our results apply to a simple matrix, without taking the limit and without n-th root
Heyouni, Mohammed. "Méthode de Hessenberg généralisée et applications." Lille 1, 1996. http://www.theses.fr/1996LIL10171.
Full textZounon, Mawussi. "On numerical resilience in linear algebra." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0038/document.
Full textAs the computational power of high performance computing (HPC) systems continues to increase by using huge number of cores or specialized processing units, HPC applications are increasingly prone to faults. This study covers a new class of numerical fault tolerance algorithms at application level that does not require extra resources, i.e., computational unit or computing time, when no fault occurs. Assuming that a separate mechanism ensures fault detection, we propose numerical algorithms to extract relevant information from available data after a fault. After data extraction, well chosen part of missing data is regenerated through interpolation strategies to constitute meaningful inputs to numerically restart the algorithm. We have designed these methods called Interpolation-restart techniques for numerical linear algebra problems such as the solution of linear systems or eigen-problems that are the inner most numerical kernels in many scientific and engineering applications and also often ones of the most time consuming parts. In the framework of Krylov subspace linear solvers the lost entries of the iterate are interpolated using the available entries on the still alive nodes to define a new initial guess before restarting the Krylov method. In particular, we consider two interpolation policies that preserve key numerical properties of well-known linear solvers, namely the monotony decrease of the A-norm of the error of the conjugate gradient or the residual norm decrease of GMRES. We assess the impact of the fault rate and the amount of lost data on the robustness of the resulting linear solvers.For eigensolvers, we revisited state-of-the-art methods for solving large sparse eigenvalue problems namely the Arnoldi methods, subspace iteration methods and the Jacobi-Davidson method, in the light of Interpolation-restart strategies. For each considered eigensolver, we adapted the Interpolation-restart strategies to regenerate as much spectral information as possible. Through intensive experiments, we illustrate the qualitative numerical behavior of the resulting schemes when the number of faults and the amount of lost data are varied; and we demonstrate that they exhibit a numerical robustness close to that of fault-free calculations. In order to assess the efficiency of our numerical strategies, we have consideredan actual fully-featured parallel sparse hybrid (direct/iterative) linear solver, MaPHyS, and we proposed numerical remedies to design a resilient version of the solver. The solver being hybrid, we focus in this study on the iterative solution step, which is often the dominant step in practice. The numerical remedies we propose are twofold. Whenever possible, we exploit the natural data redundancy between processes from the solver toperform an exact recovery through clever copies over processes. Otherwise, data that has been lost and is not available anymore on any process is recovered through Interpolationrestart strategies. These numerical remedies have been implemented in the MaPHyS parallel solver so that we can assess their efficiency on a large number of processing units (up to 12; 288 CPU cores) for solving large-scale real-life problems
Ferreira, Lago Rafael. "A study on block flexible iterative solvers with applications to Earth imaging problem in geophysics." Phd thesis, Toulouse, INPT, 2013. http://oatao.univ-toulouse.fr/10055/1/Ferreira.pdf.
Full textAdout, Robert. "Sur l'extrapolation et la convergence de la méthode GMRES." Paris 6, 2005. http://www.theses.fr/2005PA066258.
Full textSedrakian, Malhami Ani. "Vers une aide à la décision pour les méthodes itératives hybrides parallèles réutilisables." Paris 6, 2005. http://www.theses.fr/2005PA066074.
Full textTinzefte, Abdellatif. "Étude algorithmique et théorique de quelques méthodes de type Lanczos." Lille 1, 2006. https://ori-nuxeo.univ-lille1.fr/nuxeo/site/esupversions/4f702b59-cffe-4448-8753-7984d036aaba.
Full textAl, Daas Hussam. "Résolution de systèmes linéaires issus de la modélisation des réservoirs." Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS329.
Full textThis thesis presents a work on iterative methods for solving linear systems that aim at reducing the communication in parallel computing. The main type of linear systems in which we are interested arises from a real-life reservoir simulation. Both schemes, implicit and explicit, of modelling the system are taken into account. Three approaches are studied separately. We consider non-symmetric (resp. symmetric) linear systems. This corresponds to the explicit (resp. implicit) formulation of the model problem. We start by presenting an approach that adds multiple search directions per iteration rather than one as in the classic iterative methods. Then, we discuss different strategies of recycling search subspaces. These strategies reduce the global iteration count of a considerable factor during a sequence of linear systems. We review different existing strategies and present a new one. We discuss the parallel implementation of these methods using a low-level language. Numerical experiments for both sequential and parallel implementations are presented. We also consider the algebraic domain decomposition approach. In an algebraic framework, we study the two-level additive Schwarz preconditioner. We provide the algebraic explicit form of a class of local coarse spaces that bounds the spectral condition number of the preconditioned matrix by a number pre-defined
Mouhaidali, Amjad. "Contribution à la modélisation des câbles HVDC pour la simulation des transitoires électromagnétiques." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT125.
Full textThe integration of new technologies in the electric grids made them more and more complex, and most likely future growth of power grids will be based more on underground cables than overhead lines. One problem here, is that the mathematical model for electromagnetic simulation of power cables still has some shortcomings regarding stability, accuracy and passivity.In this thesis, we evaluate the cable parameters using analytical and numerical methods. The cable physical parameter dependency on frequency and temperature is investigated and a parametric study is done. The resulting frequency dependent admittance and propagation matrices describes accurately the cable behavior over a wide frequency range.The Wide Band model is reformulated using an original and robust fitting method. This method is based on the rational Krylov approximation algorithm. The admittance and propagation matrices are fitted in the frequency domain using the Krylov based method. We found that this approximation method is more accurate than that used in the original implementation of the wide band model known as Vector Fitting. Krylov based approximation showed an enhancement in the fitting and especially at low frequency for HVDC transmission. Time domain simulation based on the Numerical Laplace Transform are used to assess the accuracy of the aforementioned model.An original and robust passivity enforcement algorithm is proposed to fulfill the passivity criteria on a passivity violated model. This algorithm tries to iteratively improve the accuracy of the rational approximation that relates to the passivity violation. It was shown that after few iterations the algorithm renders a passive and a stable cable model.Finally, based on these developments, further research themes are proposed
Barkouki, Houda. "Rational Lanczos-type methods for model order reduction." Thesis, Littoral, 2016. http://www.theses.fr/2016DUNK0440/document.
Full textNumerical solution of dynamical systems have been a successful means for studying complex physical phenomena. However, in large-scale setting, the system dimension makes the computations infeasible due to memory and time limitations, and ill-conditioning. The remedy of this problem is model reductions. This dissertations focuses on projection methods to efficiently construct reduced order models for large linear dynamical systems. Especially, we are interesting by projection onto unions of Krylov subspaces which lead to a class of reduced order models known as rational interpolation. Based on this theoretical framework that relate Krylov projection to rational interpolation, four rational Lanczos-type algorithms for model reduction are proposed. At first, an adaptative rational block Lanczos-type method for reducing the order of large scale dynamical systems is introduced, based on a rational block Lanczos algorithm and an adaptive approach for choosing the interpolation points. A generalization of the first algorithm is also given where different multiplicities are consider for each interpolation point. Next, we proposed another extension of the standard Krylov subspace method for Multiple-Input Multiple-Output (MIMO) systems, which is the global Krylov subspace, and we obtained also some equations that describe this process. Finally, an extended block Lanczos method is introduced and new algebraic properties for this algorithm are also given. The accuracy and the efficiency of all proposed algorithms when applied to model order reduction problem are tested by means of different numerical experiments that use a collection of well known benchmark examples
Roland, Christophe. "Méthodes d'accélération de convergence en analyse numérique et en statistique." Lille 1, 2005. https://pepite-depot.univ-lille.fr/LIBRE/Th_Num/2005/50376-2005-Roland.pdf.
Full textSadek, El Mostafa. "Méthodes itératives pour la résolution d'équations matricielles." Thesis, Littoral, 2015. http://www.theses.fr/2015DUNK0434/document.
Full textIn this thesis, we focus in the studying of some iterative methods for solving large matrix equations such as Lyapunov, Sylvester, Riccati and nonsymmetric algebraic Riccati equation. We look for the most efficient and faster iterative methods for solving large matrix equations. We propose iterative methods such as projection on block Krylov subspaces Km(A, V ) = Range{V,AV, . . . ,Am−1V }, or block extended Krylov subspaces Kem(A, V ) = Range{V,A−1V,AV,A−2V,A2V, · · · ,Am−1V,A−m+1V }. These methods are generally most efficient and faster for large problems. We first treat the numerical solution of the following linear matrix equations : Lyapunov, Sylvester and Stein matrix equations. We have proposed a new iterative method based on Minimal Residual MR and projection on block extended Krylov subspaces Kem(A, V ). The extended block Arnoldi algorithm gives a projected minimization problem of small size. The reduced size of the minimization problem is solved by direct or iterative methods. We also introduced the Minimal Residual method based on the global approach instead of the block approach. We projected on the global extended Krylov subspace Kem(A, V ) = Span{V,A−1V,AV,A−2V,A2V, · · · ,Am−1V,A−m+1V }. Secondly, we focus on nonlinear matrix equations, especially the matrix Riccati equation in the continuous case and the nonsymmetric case applied in transportation problems. We used the Newton method and MINRES algorithm to solve the projected minimization problem. Finally, we proposed two new iterative methods for solving large nonsymmetric Riccati equation : the first based on the algorithm of extended block Arnoldi and Galerkin condition, the second type is Newton-Krylov, based on Newton’s method and the resolution of the large matrix Sylvester equation by using block Krylov method. For all these methods, approximations are given in low rank form, wich allow us to save memory space. We have given numerical examples that show the effectiveness of the methods proposed in the case of large sizes
Boillod-Cerneux, France. "Nouveaux algorithmes numériques pour l'utilisation efficace des architectures de calcul multi-coeurs et hétérogènes." Thesis, Lille 1, 2014. http://www.theses.fr/2014LIL10137/document.
Full textThe supercomputers architectures and programming paradigms have dramatically evolve during the last decades. Since we have reached the Petaflopic scale, we forecast to overcome the Exaflopic scale. Crossing this new scale implies many drastic changes, concerning the overall High Performance Computing scientific fields. In this Thesis, we focus on the eigenvalue problems, implied in most of the industrial simulations. We first propose to study and caracterize the Explicitly Restarted Arnoldi Method convergence. Based on this algorithm, we re-use efficiently the computed Ritz-Eigenvalues to accelerate the ERAM convergence onto the desired eigensubspace. We then propose two matrix generators, starting from a user-imposed spectrum. Such matrix collections are used to numerically check and approve extrem-scale eigensolvers, as well as measure and improve their parallel performance on ultra-scale supercomputers
Moulin, Johann. "On the flutter bifurcation in laminar flows : linear and nonlinear modal methods." Thesis, Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAX093.
Full textThe flutter instability has been the focus of numerous works since the middle of the twentieth century, due to its critical application in aeronautics. Flutter is classically described as a linear instability using potential flow models, but viscous and nonlinear fluid effects may both crucially impact this aeroelastic phenomenon.The first part of this thesis is devoted to the development of theoretical and numerical methods for analyzing the linear and nonlinear dynamics of a ``typical aeroelastic section'' --- a heaving and pitching spring-mounted plate --- immersed in a two-dimensional laminar flow modeled by the incompressible Navier--Stokes equations.First, we develop a semi-analytical weakly nonlinear analysis to efficiently study the small amplitude regime. Second, we develop a harmonic balance-type method, known as the Time Spectral Method (TSM), in order to tackle highly-nonlinear periodic flutter solutions. The challenging task of solving the TSM equations is tackled via a time-parallel Newton--Krylov approach in combination with a new, so-called block-circulant preconditioner.The second part of the thesis focuses on the physical investigation of the flutter bifurcation. We start by revisiting the linear stability problem using a Navier--Stokes fluid model allowing to highlight, in particular, the effect of viscosity.We continue our route on the flutter bifurcation by investigating the effect of fluid nonlinearities: low solid-to-fluid mass ratios and increasing Reynolds numbers foster subcritical bifurcations.We conclude our study by investigating the appearance of low-frequency amplitude modulations on top of a previously established periodic flutter solution. We explain this behavior by a (Floquet) linear instability of periodic solutions.The last part of the thesis aims at initiating the extension of the different methods previously evoked to large-scale three-dimensional configurations. As a first step towards this long-term goal, we develop an open-source massively parallel tool, able to perform hydrodynamic (the structure is fixed) linear stability analysis of three-dimensional flows possessing several tens of millions of degrees of freedom
Molina-Sepulveda, Roberto. "Hybridization of FETI Methods." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066455/document.
Full textIn this work new domain decomposition methods and new implementations for existing methods are developed. A new method based on previous domain decomposition methods is formulated. The classic FETI plus FETI-2LM methods are used to build the new Hybrid-FETI. The basic idea is to develop a new algorithm that can use both methods at the same time by choosing in each interface the most suited condition depending on the characteristics of the problem. By doing this we search to have a faster and more robust code that can work with configurations that the base methods will not handle it optimally by himself. The performance is tested on a contact problem. The following part involves the development of a new implementation for the S-FETI method, the idea is to reduce the memory usage of this method, to make it able to work in larger problem. Different variation for this method are also proposed, all searching the reduction of directions stored each iteration of the iterative method. Finally, an extension of the FETI-2LM method to his block version as in S-FETI, is developed. Numerical results for the different algorithms are presented
Wu, Xinzhe. "Contribution à l’émergence de nouvelles méthodes parallèles et réparties intelligentes utilisant un paradigme de programmation multi-niveaux pour le calcul extrême." Thesis, Lille 1, 2019. http://www.theses.fr/2019LIL1I010/document.
Full textKrylov iterative methods are frequently used on High-Performance Computing (HPC) systems to solve the extremely large sparse linear systems and eigenvalue problems from science and engineering fields. With the increase of both number of computing units and the heterogeneity of supercomputers, time spent in the global communication and synchronization severely damage the parallel performance of iterative methods. Programming on supercomputers tends to become distributed and parallel. Algorithm development should consider the principles: 1) multi-granularity parallelism; 2) hierarchical memory; 3) minimization of global communication; 4) promotion of the asynchronicity; 5) proposition of multi-level scheduling strategies and manager engines to handle huge traffic and improve the fault tolerance. In response to these goals, we present a distributed and parallel multi-level programming paradigm for Krylov methods on HPC platforms. The first part of our work focuses on an implementation of a scalable matrix generator to create test matrices with customized eigenvalue for benchmarking iterative methods on supercomputers. In the second part, we aim to study the numerical and parallel performance of proposed distributed and parallel iterative method. Its implementation with a manager engine and runtime can handle the huge communication traffic, fault tolerance, and reusability. In the third part, an auto-tuning scheme is introduced for the smart selection of its parameters at runtime. Finally, we analyse the possibility to implement the distributed and parallel paradigm by a graph-based workflow runtime environment
Jorti, Zakariae. "Fast solution of sparse linear systems with adaptive choice of preconditioners." Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS149.
Full textThis thesis analyzes the use of adaptive preconditioned Krylov methods in applications which can be modeled by partial differential equations. Preconditioning is generally essential for efficiently solving large sparse nonlinear systems of equations. However, the optimality of the available preconditioners is not guaranteed for all uses due to the changing nature of the linearized operator. This thesis explores some types of preconditioners and solve procedures that can adapt to the complexity of linear systems using information from a posteriori error estimates. First, we propose global and local adaptive strategies based on a posteriori error estimation and a hybrid block-jacobi and ILU(0) preconditioner. Second, the a posteriori error estimation is used to partition the matrix, and a Schur complement-based approach is used for the preconditioning of the block with a high error. Then, we introduce a variant of this latter approach which replaces the costly exact factorizations by low-rank approximations. We also define an adaptive preconditioner based on a posteriori error estimation that allows to control a local algebraic error norm. Finally, we prove the efficiency of our adaptive strategies on two-dimensional reservoir simulation examples for heterogeneous porous media
Archid, Atika. "Méthodes par blocs adaptées aux matrices structurées et au calcul du pseudo-inverse." Thesis, Littoral, 2013. http://www.theses.fr/2013DUNK0394/document.
Full textWe study, in this thesis, some numerical block Krylov subspace methods. These methods preserve geometric properties of the reduced matrix (Hamiltonian or skew-Hamiltonian or symplectic). Among these methods, we interest on block symplectic Arnoldi, namely block J-Arnoldi algorithm. Our main goal is to study this method, theoretically and numerically, on using ℝ²nx²s as free module on (ℝ²sx²s, +, x) with s ≪ n the size of block. A second aim is to study the approximation of exp (A)V, where A is a real Hamiltonian and skew-symmetric matrix of size 2n x 2n and V a rectangular matrix of size 2n x 2s on block Krylov subspace Km (A, V) = blockspan {V, AV,...Am-1V}, that preserve the structure of the initial matrix. this approximation is required in many applications. For example, this approximation is important for solving systems of ordinary differential equations (ODEs) or time-dependant partial differential equations (PDEs). We also present a block symplectic structure preserving Lanczos method, namely block J-Lanczos algorithm. Our approach is based on a block J-tridiagonalization procedure of a structured matrix. We propose algorithms based on two normalization methods : the SR factorization and the Rj R factorization. In the last part, we proposea generalized algorithm of Greville method for iteratively computing the Moore-Penrose inverse of a rectangular real matrix. our purpose is to give a block version of Greville's method. All methods are completed by many numerical examples
Rey, Valentine. "Pilotage de stratégies de calcul par décomposition de domaine par des objectifs de précision sur des quantités d’intérêt." Thesis, Université Paris-Saclay (ComUE), 2015. http://www.theses.fr/2015SACLN018/document.
Full textThis research work aims at contributing to the development of verification tools in linear mechanical problems within the framework of non-overlapping domain decomposition methods.* We propose to improve the quality of the statically admissible stress field required for the computation of the error estimator thanks to a new methodology of stress reconstruction in sequential context and thanks to optimizations of the computations of nodal reactions in substructured context.* We prove guaranteed upper and lower bounds of the error that separates the algebraic error (due to the iterative solver) from the discretization error (due to the finite element method) for both global error measure mentand goal-oriented error estimation. It enables the definition of a new stopping criterion for the iterative solver which avoids over-resolution.* We benefit the information provided by the error estimator and the Krylov subspaces built during the resolution to set an auto-adaptive strategy. This strategy consists in sequel of resolutions and takes advantage of adaptive remeshing and recycling of search directions .We apply the steering of the iterative solver by objective of precision on two-dimensional mechanical examples
Bargiacchi, Sandrine. "Résolution de grands systèmes : du linéaire au non linéaire." Toulouse 3, 2004. http://www.theses.fr/2004TOU30049.
Full textLe, Calvez Caroline. "Accélération de méthodes de Krylov pour la résolution de systèmes linéaires creux sur machines parallèles." Lille 1, 1998. https://pepite-depot.univ-lille.fr/LIBRE/Th_Num/1998/50376-1998-225.pdf.
Full textIvanova, Elena. "Identification de systèmes multivariables par modèle non entier en utilisant la méthode des sous-espaces." Thesis, Bordeaux, 2017. http://www.theses.fr/2017BORD0561/document.
Full textThe identification of systems by fractional models was initiated in the 1990s and various results have been obtained since. Nevertheless, most of these results are based on prediction error methods (PEM) of identification, based on the minimization of the norm of the estimation error. Apparent in 1996, the subspace methods are relatively new in the theory of the identification of linear systems. Based on geometric projections and linear algebra, they present an alternative to classical methods based on linear or nonlinear regression. They allow estimating the matrices of the state-space representation of a system. In the context of fractional systems, a pseudo-state-space representation generalizes the notion of state-space representation by introducing an additional parameter which is the commensurable order.Currently, the subspace method for non-integer systems has only been applied inthe time domain. It is then developed in this thesis for such a class of systems in the frequency domain. Moreover, since non-integer systems are continuous time systems, datapre-filtering is necessary to respect the causality of the signals and to be able to realize the identification. A study of the different filtering methods in the context of subspaceidentification is then carried out in order to deduce their advantages and disadvantages in the time domain. Finally, the method has been applied to a thermal diffusion system.The obtained models are generalized for several input heat flows, considering their temperature available at several measurement points
Mercère, Guillaume. "Contribution à l'identification récursive des systèmes par l'approche des sous-espaces." Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2004. http://tel.archives-ouvertes.fr/tel-00007958.
Full textBelhadji, Ayoub. "Echantillonnage des sous-espaces à l’aide des processus ponctuels déterminantaux." Thesis, Ecole centrale de Lille, 2020. http://www.theses.fr/2020ECLI0021.
Full textDeterminantal point processes are probabilistic models of repulsion.These models were studied in various fields: random matrices, quantum optics, spatial statistics, image processing, machine learning and recently numerical integration.In this thesis, we study subspace sampling using determinantal point processes. This problem takes place within the intersection of three sub-domains of approximation theory: subset selection, kernel quadrature and kernel interpolation. We study these classical topics, through a new interpretation of these probabilistic models: a determinantal point process is a natural way to define a random subspace. Beside giving a unified analysis to numerical integration and interpolation under determinantal point processes, this new perspective allows to work out the theoretical guarantees of several approximation algorithms, and to prove their optimality in some settings
Duminil, Sébastien. "Extrapolation vectorielle et applications aux équations aux dérivées partielles." Phd thesis, Université du Littoral Côte d'Opale, 2012. http://tel.archives-ouvertes.fr/tel-00790115.
Full textGilson, Marion. "Identification des systèmes en boucle fermée : contributions aux méthodes de compensation de biais et des sous-espaces." Nancy 1, 2000. http://www.theses.fr/2000NAN10119.
Full textThe thesis deals with closed-loop identification of SISO or MIMO systems, represented by a linear time-invariant-model either in transfer or state-space forms. This work is divided into three main parts. The first part gives key issues associated with closed-loop system identification as well as a bibliographic synthesis of the different available methods, classicall divided into three broad categories and referred to as direct, indirect and joint inout/output approaches. The second part focuses on the so-called bias-eliminated least-squares method for closed-loop identification of a transfer function by an indirect approach. It basically consists in estimating and then removing the bias introduced by the least-squares algorithm. The contribution of this chapter is twofold. At first proposition aims as enlightening the interpretation of those bias eliminated techniques by demonstrating their membership to the instrumental variable estimator class. A second proposition develops an extension of the previous method to the closed-loop continuous-time system identification, from sampled input/output data. Then, the last part of this thesis adresses the crucial (open) point of analyzing and assessing the quality of a nominal closed-loop state-space model stemmed from a subspace technique. In this respect, the identification algorithm is formulated in terms of a criterion minimisaton. This formulation is used on the one hand, to develop an algorithm improvement for estimating the nominal model. On the second hand, several methofd for estimating uncertainty regions of nominal model invariant parameters are proposed
Cabuzel-Zèbre, Catherine. "Résolution d'inclusions variationnelles par des méthodes multipoints et des méthodes classiques dans le cadre sous-analytique." Antilles-Guyane, 2008. http://www.theses.fr/2008AGUY0239.
Full textThis work deals with seminumerical methods for soIving variational inclusions of the form zero in f(x)+F(x) where the function f and the set-valued map F are bath acting in a Banach space. The fisrt part, we recall sorne resulls on Upschitz continuity, directional derivatives, semialgebraic and subanalytic sets and functions and divided differences; then we give some results on set-valued analysis. In the second part, we present the muItipoint iterative method and we deveIop the soIving of variational inclusions by this method in the Lipschitz case, the HöIder case and the center-Hölder case. The third part is dedicated to the study of classical methods in the subanalytic case. Newton's method was the subject of many works concerning the sollving of equations or variational inclusions, but the case where fis not Frechet derivable or does not admit divided dilferences has not been studied 50 far; that is why we investigate a Newton type method when f is subanalytic. Afterwards, our study concerns a perturbed probIem of the form zero in f(x)+g(x)+F(x), where all the functions involved are acting in R^n. We analyse a NewIon-secant type method and two variants: a regula-falsi method and an acceleration of the previous method. Then we present a Stetrensen type method and finally an iterative method in the case where the function g is Lipschitz
Lachaud, Antoine. "Discrimination robuste par méthode à noyaux." Thesis, Rouen, INSA, 2015. http://www.theses.fr/2015ISAM0015/document.
Full textThis thesis aims at finding classification rnodeIs which include explanatory elements. More specifically the proposed solution consists in merging a regularization path algorithm called DRSVM with a kernel approach called KERNEL BASIS. The first part of the thesis focuses on improving an algorithm called DRSVM from a reformulation of the thanks to the suh-differential theory. The second part of the thesis describes the extension of DRSVM afgorithm under a KERNEL BASIS framework via a dictionary approach. Finally, a series of experiments are conducted in order to validate the interpretable aspect of the rnodel
Hakem, Assia. "Méthode de projection des données pour le diagnostic des systèmes linéaires et bilinéaires." Thesis, Lille 1, 2014. http://www.theses.fr/2014LIL10035/document.
Full textIn this thesis we are interested in detecting, isolating and estimating faults (sensors, actuators and internal faults) in systems modeled as linear and bilinear systems. The method we propose (called MPD Data Projection Method), requires knowledge of the behavioral model structure but does not need to know the parameter values of this model. Residuals are generated by matrix projection techniques using only the input-output measured data. This method can be directly implemented on applications of the same type without the parameter identifications of each system. This method could be very useful for testing systems at the end of the production line or to be located on a park (group) of identical machines. It could also be useful for systems with parameters difficult to identify. Internal faults (assumed abrupt and invariants, that is to say corresponding to a constant bias parameters) lead to different dynamics corresponding to modes of faulty operation. The diagnostic problem then reduces to a problem of estimation of the switching times and recognition of the active mode at each time instant
Klaja, Hubert. "Autour des projections orthogonales : image numérique, principe d’incertitude et problème du sous-espace invariant." Thesis, Lille 1, 2014. http://www.theses.fr/2014LIL10036/document.
Full textIn this PhD thesis in Operator Theory, we are interested in orthogonal projections, numerical ranges of operators acting on a Hilbert space, uncertainty principles, the invariant subspace problem and perturbations of diagonal operators. After an introductory chapter, we investigate the numerical range of a product of two orthogonal projections and possible applications. We give an explicit formula of the numerical range for a product of orthogonal projections depending on its spectrum. We show how to reconstruct some parts of the spectrum of the product of orthogonal projections from its numerical range. As a consequence, we give new characterizations of the speed of convergence in the method of alternating projections (von Neumann-Halperin like Theorems), and a new characterization of annihilating pairs (which is a formulation of the uncertainty principle). In the next chapter, we study differences of orthogonal projections. We give a caracterisation of operators that can be expressed as a difference of orthogonal projections. We apply these results to some unitary operators (including the bilateral shift) by writing them as linear combinations of orthogonal projections. Then we apply again these results by establishing a new uncertainty principle for orthogonal polynomials, improving recent results of W. Erb.In the last part of this thesis, we prove the exitence of hyperinvariant subspaces for some compact perturbations of multiplication operators. This generalize former results of Fang-Xia and Foias-Jung-Ko-Pearcy. Finally, we show the existence of rank-one perturbations of diagonal operators without eigenvalues, solving in this way an open problem of E. Ionascu
Gautier, Guillaume. "Diagnostic vibratoire des systèmes mécaniques par subspace fitting." Thesis, Tours, 2015. http://www.theses.fr/2015TOUR4026/document.
Full textIn this thesis, a subspace fitting (SF) method is presented for the identification of mechanical parameters and assessment of the health condition of vibrating structures. The SF method attempts to extract, from subspace identification methods (4SID), a system observability matrix of the system and correlate them with a theoretical observability matrix. The originality of this work is to obtain the theoretical observability matrix from a finite element model (EF) of the structure. By adjusting unknown parameters of the FE model, the mechanical properties of the vibrating structure are identified. Computational costs of such a procedure are reduced by considering a model reduction method based on the excitations and sensors location. The method is evaluated for the identification of natural frequencies of a vibrating structure. Numerical and experimental applications are assessed to show the relevance of such an approach. In particular, it is highlighted that the SF method can accurately identify the natural frequencies of a structure to high noise levels
Afri, Chouaib. "Observateurs adaptatifs pour l'identification en ligne et l'observation des systèmes linéaires." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1302/document.
Full textIn this thesis, we study the problem of identification of a linear dynamical system. First, we survey various methods that have been developed in the literature. We focus more particularly on methods named adaptive observers. Secondly we present an approach which combines subspace identification methods and adaptive observers. This new method is interesting since it allows us to identify MIMO systems in an arbitrary basis. The convergence of this algorithm is demonstrated using the persistent excitation notions. In the third chapter we introduce a new method that is inspired from nonlinear Luenberger observers developed in recent years. This new algorithm is different from the existing algorithms since the parameters and the systemstatus are estimated simultaneously. We demonstrate the robustness of this approach. The convergence of the algorithm is obtained if the system inputs satisfy a differential excitation hypothesis. All these algorithms are evaluated and implemented on an experimental bench
Rasheed, Amer. "Solidification Dendritique de Mélanges Binaires de Métaux sous l'Action de Champs Magnétique: Modélisation, Analyse Mathématique et Numérique." Phd thesis, INSA de Rennes, 2010. http://tel.archives-ouvertes.fr/tel-00565743.
Full textAyala, Obregón Alan. "Complexity reduction methods applied to the rapid solution to multi-trace boundary integral formulations." Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS581.
Full textIn this thesis, we provide complexity reduction techniques for the solution of Boundary Integral Equations (BIE). In particular, we focus on BIE arising from the modeling of acoustic and electromagnetic problems via Boundary Element Methods (BEM). We use the local multi-trace formulation which is friendly to operator preconditioning. We find a closed form inverse of the local multi-trace operator for a model problem and then we propose this inverse operator for preconditioning general scattering problems. Moreover, we show that the local multi-trace formulation is stable for Maxwell equations posed on a particular domain configuration. For general problems where BEM are applied, we propose to use the framework of hierarchical matrices, which are constructed using cluster trees and allow to represent the original matrix in such a way that submatrices that admit low-rank approximations (admissible blocks) are well identified. We introduce a technique called geometric sampling which uses cluster trees to create accurate linear-time CUR algorithms for the compression and matrix-vector product acceleration of admissible matrix blocks, and which are oriented to develop parallel communication-avoiding algorithms. We also contribute to the approximation theory of QR and subspace iteration methods; for the former we provide new bounds for the approximation error, and for the later we solve an open question in the literature consisting in proving that the approximation of singular vectors exponentially converges. Finally, we propose a technique called affine low-rank approximation intended to increase the accuracy of classical low-rank approximation methods
Mendoume, Minko Ignace Davy. "Identification des systèmes dynamiques stochastiques." Phd thesis, Clermont-Ferrand 2, 2005. https://tel.archives-ouvertes.fr/tel-00676619/document.
Full textElvira, Clément. "Modèles bayésiens pour l’identification de représentations antiparcimonieuses et l’analyse en composantes principales bayésienne non paramétrique." Thesis, Ecole centrale de Lille, 2017. http://www.theses.fr/2017ECLI0016/document.
Full textThis thesis proposes Bayesian parametric and nonparametric models for signal representation. The first model infers a higher dimensional representation of a signal for sake of robustness by enforcing the information to be spread uniformly. These so called anti-sparse representations are obtained by solving a linear inverse problem with an infinite-norm penalty. We propose in this thesis a Bayesian formulation of anti-sparse coding involving a new probability distribution, referred to as the democratic prior. A Gibbs and two proximal samplers are proposed to approximate Bayesian estimators. The algorithm is called BAC-1. Simulations on synthetic data illustrate the performances of the two proposed samplers and the results are compared with state-of-the art methods. The second model identifies a lower dimensional representation of a signal for modelisation and model selection. Principal component analysis is very popular to perform dimension reduction. The selection of the number of significant components is essential but often based on some practical heuristics depending on the application. Few works have proposed a probabilistic approach to infer the number of significant components. We propose a Bayesian nonparametric principal component analysis called BNP-PCA. The proposed model involves an Indian buffet process to promote a parsimonious use of principal components, which is assigned a prior distribution defined on the manifold of orthonormal basis. Inference is done using MCMC methods. The estimators of the latent dimension are theoretically and empirically studied. The relevance of the approach is assessed on two applications
Paulus, Caroline. "Filtrage de données sismiques multicomposantes et estimation de la polarisation." Phd thesis, Grenoble INPG, 2006. http://tel.archives-ouvertes.fr/tel-00204504.
Full textIls peuvent enregistrer le déplacement dans plusieurs directions de l'espace ainsi que les variations de pression.
Le développement de traitements adaptés à ce type de données est nécessaire.
Le but de ce travail de thèse est de développer une méthode permettant d'une part le débruitage de données sismiques multicomposantes, la séparation des différents champs d'ondes ou encore l'estimation de la polarisation des ondes et de leur direction d'arrivée (DOA).
Cette méthode, appelée filtrage matriciel large-bande multicomposante, dérivée de la méthode monocomposante, prend en compte l'information de polarisation et traite les différentes composantes de façon globale et non indépendamment.
Le principe utilisé est celui de la décomposition en valeurs propres d'une matrice spectrale pour permettre une séparation efficace de l'espace des données de départ en deux espaces complémentaires (sous-espace signal et sous-espace bruit).