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Добірка наукової літератури з теми "Équation d'ondes élastique"
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Дисертації з теми "Équation d'ondes élastique"
Lehmann, Fanny. "A surrogate model of elastic wave propagation to quantify uncertainties in seismic hazard analysis." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPAST074.
Повний текст джерелаThe propagation of seismic waves in the ground is subject to many sources of uncertainties, ranging from the uncertain activity of geological faults to the incomplete knowledge of mechanical properties inside the Earth's crust. To properly assess seismic hazard, it then becomes essential to quantify how uncertainties influence the intensity of ground motion generated by earthquakes.In areas with low-to-moderate seismicity, like most regions in metropolitan France, seismic records are too sparse to evaluate ground motion uncertainties. In this situation, numerical simulations are the only option to estimate ground motion intensity, but their high computational costs prevent most uncertainty analyses. In this thesis, we design a surrogate model that can replace the numerical solver by drastically reducing the computational costs while preserving its flexibility and a satisfying accuracy.We first illustrate the influence of geological heterogeneities on ground motion intensity in the context of the Mw4.9 Le Teil earthquake (Ardèche, France, 2019). Heterogeneities are added to a regional geological model in the form of random fields, and we show that it generates more realistic ground motion. However, heterogeneities also lead to a large variability between samples.To study this variability systematically, we build a database of 30,000 heterogeneous 3D geological models, and inside each geology, seismic waves are propagated from a random source using the spectral element code SEM3D. The database is then used to train a surrogate model in a purely data-driven framework.To design the surrogate model, we propose an extension of the Fourier Neural Operator called the Multiple Input Fourier Neural Operator (MIFNO). The MIFNO takes as inputs a 3D geology and a vector of source parameters to predict 3D ground motion. Ground motion is a time-dependent surface wavefield, but we do not need any time iteration thanks to a depth-to-time conversion. We characterize the MIFNO prediction error and explore the MIFNO generalization ability to out-of-distribution data.We finally take advantage of transfer learning to further improve the MIFNO accuracy in the context of the Le Teil earthquake. With this fine-tuned surrogate model, we obtain statistical distributions of several quantities of interest in seismic hazard assessment. They are coherent with numerical simulations and provide confidence intervals that were out of reach with existing methods
Bécache, Eliane. "Resolution par une methode d'equations integrales d'un probleme de diffraction d'ondes elastiques transitoires par une fissure." Paris 6, 1991. http://www.theses.fr/1991PA066022.
Повний текст джерелаDupuy-Frank. "Ambigui͏̈tés dans la diffusion des ondes élastiques dans l'approximation de Helmholtz." Montpellier 2, 1993. http://www.theses.fr/1993MON20089.
Повний текст джерелаGranat, Cristel. "Formulation variationelle par équations intégrales pour des problèmes de diffraction d'ondes acoustiques et élastiques dans un demi-plan." Compiègne, 2000. http://www.theses.fr/2000COMP1298.
Повний текст джерелаGodoy, Eduardo. "Modélisation mathématique et simulation numérique avancée des phénomènes de propagation d'ondes dans les médias élastiques sans limite." Phd thesis, Ecole Polytechnique X, 2010. http://pastel.archives-ouvertes.fr/pastel-00006252.
Повний текст джерелаPoisson, Olivier. "Calcul des pôles de résonance associés à la diffraction d'ondes acoustiques et élastiques par un obstacle en dimension 2." Paris 9, 1992. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=1992PA090018.
Повний текст джерелаBaron, Cécile. "Le développement en série de Peano du matricant pour l'étude de la propagation des ondes élastiques en milieux à propriétés continûment variables." Bordeaux 1, 2005. http://www.theses.fr/2005BOR13036.
Повний текст джерелаBoillot, Lionel. "Contributions à la modélisation mathématique et à l'algorithmique parallèle pour l'optimisation d'un propagateur d'ondes élastiques en milieu anisotrope." Thesis, Pau, 2014. http://www.theses.fr/2014PAUU3043/document.
Повний текст джерелаThe most common method of Seismic Imaging is the RTM (Reverse Time Migration) which depends on wave propagation simulations in the subsurface. We focused on a 3D elastic wave propagator in anisotropic media, more precisely TTI (Tilted Transverse Isotropic). We directly worked in the Total code DIVA (Depth Imaging Velocity Analysis) which is based on a discretization by the Discontinuous Galerkin method and the Leap-Frog scheme, and developed for intensive parallel computing – HPC (High Performance Computing). We choose to especially target two contributions. Although they required very different skills, they share the same goal: to reduce the computational cost of the simulation. On one hand, classical boundary conditions like PML (Perfectly Matched Layers) are unstable in TTI media. We have proposed a formulation of a stable ABC (Absorbing Boundary Condition) in anisotropic media. The technique is based on slowness curve properties, giving to our approach an original side. On the other hand, the initial parallelism, which is based on a domain decomposition and communications by message passing through the MPI library, leads to load-imbalance and so poor parallel efficiency. We have fixed this issue by replacing the paradigm for parallelism by the use of task-based programming through runtime system. This PhD thesis have been done in the framework of the research action DIP (Depth Imaging Partnership) between the Total oil company and Inria
Saouri, Fatima-Zahra. "Stabilisation de quelques systèmes élastiques : analyse spectrale et comportement asymptotique." Nancy 1, 2000. http://docnum.univ-lorraine.fr/public/SCD_T_2000_0279_SAOURI.pdf.
Повний текст джерелаHamitou, Okba. "Efficient preconditioning method for the CARP-CG iterative solver for the solution of the frequency-domain visco-elastic wave equation." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM087/document.
Повний текст джерелаA robust and efficient wave modeling method is the cornerstone of high resolution seismic inversion methods such as the frequency-domain Full Waveform Inversion (Virieux, 2009). After discretization, frequency-domain wave modeling amounts to the solution of large (up to several billion of unknowns for realistic case studies), sparse, indefinite and ill-conditioned linear systems. Furthermore, seismic inversion methods require the solution of this problem for numerous sources (from several thousands up to tens of thousands). In the acoustic approximation, 3D real case studies can be handled efficiently using direct solvers. However because of their tremendous intrinsic memory requirements, they are not yet adapted to the solution of the 3D elastodynamics equations. Iterative solvers provide an alternative to direct solvers. However, they require a preconditioning strategy to ensure convergence for the frequency-domain wave equation. Besides, multiple right-hand sides linear systems are not treated as efficiently as direct solvers do.In this thesis, we are interested in the use of a robust iterative solver adapted to the solution of these systems called CARP-CG (Gordon, 2010). The CARP-CG method has shown robust convergence properties for 2D and 3D elastic problems in highly heterogeneous media compared to standard Krylov methods such as GMRES or Bi-CGSTAB which require the use of a preconditioner to ensure convergence (Li, 2015). Despite the good convergence properties of CARP-CG, the latter still requires a large number of iterations to reach sufficient accuracy. I introduce an efficient preconditioning strategy adapted to the CARP-CG method and the frequency-domain wave problem. This preconditioner is computed as a sparse approximate inverse of a strongly damped wave propagation operator. The computation of the preconditioner is performed in a massively parallel algorithm for distributed memory architectures.The efficiency of the preconditioner is evaluated on several case studies. First, applications are performed on realistic synthetic models in the 2D visco-acoustic approximation (up to $40$ Hz) and the 2D visco-elastic approximation (up to $20$ Hz). These studies show that the CARP-CG method together with the preconditioning strategy is robust and efficient. The number of iterations is significantly reduced (up to a factor $9$) enabling a speedup in the computation time by a factor up to $3.5$. Second, this method is investigated in the 3D elastic approximation on a realistic synthetic case study on the range of frequencies 1.25 to 7.5 Hz. Very encouraging results are obtained with a significant reduction in the number of iterations. A slow increase of the number of iterations with respect to the frequency is noted.This preconditioning strategy adapted to the CARP-CG method implies larger memory requirements. However, this extra memory cost remains one order lower compared to direct solver memory requirement, and should be affordable on standard HPC facilities. The main bottleneck preventing from the possible use of this iterative solver for 3D elastic FWI remains the computation time for the wave equation solves