Global Carleman estimates for waves and applications

In this article, we extensively develop Carleman estimates for the wave equation and give some applications. We focus on the case of an observation of the flux on a part of the boundary satisfying the Gamma conditions of Lions. We will then consider two applications. The first one deals with the exact controllability problem for the wave equation with potential. Following the duality method proposed by Fursikov and Imanuvilov in the context of parabolic equations, we propose a constructive method to derive controls that weakly depend on the potentials. The second application concerns an inverse problem for the waves that consists in recovering an unknown time-independent potential from a single measurement of the flux. In that context, our approach does not yield any new stability result, but proposes a constructive algorithm to rebuild the potential. In both cases, the main idea is to introduce weighted functionals that contain the Carleman weights and then to take advantage of the freedom on the Carleman parameters to limit the influences of the potentials.Comment: 31 page

Convergent algorithm based on Carleman estimates for the recovery of a potential in the wave equation.

International audienceThis article develops the numerical and theoretical study of the reconstruction algorithm of a potential in a wave equation from boundary measurements, using a cost functional built on weighted energy terms coming from a Carleman estimate. More precisely, this inverse problem for the wave equation consists in the determination of an unknown time-independent potential from a single measurement of the Neumann derivative of the solution on a part of the boundary. While its uniqueness and stability properties are already well known and studied, a constructive and globally convergent algorithm based on Carleman estimates for the wave operator was recently proposed in [BdBE13]. However, the numerical implementation of this strategy still presents several challenges, that we propose to address here

Un résultat de stabilité pour la récupération d'un paramètre du système de la viscoélasticité 3D

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Reconstruction of a constitutive law for rubber from in silico experiments using Ogden's laws

International audienceThis article deals with the following data assimilation problem: construct an analytical approximation of a numerical constitutive law in three-dimensional nonlinear elasticity. More precisely we are concerned with a micro-macro model for rubber. Macroscopic quantities of interest such as the Piola-Kirchhoff stress tensor can be approximated for any value of the strain gradient by numerically solving a nonlinear PDE. This procedure is however computationally demanding. Hence, although conceptually satisfactory, this physically-based model is of no direct practical use. The aim of this article is to circumvent this difficulty by proposing a numerical strategy to reconstruct from in silico experiments an accurate analytical proxy for the micro-macro constitutive law

Numerical Modeling and High Speed Parallel Computing: New Perspectives for Tomographic Microwave Imaging for Brain Stroke Detection and Monitoring

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient based) with successive solutions of a direct problem such as the accurate modeling of a whole-microwave measurement system. Moreover, a sufficiently high number of unknowns is required to accurately represent the solution. As the system will be used for detecting the brain stroke (ischemic or hemorrhagic) as well as for monitoring during the treatment, running times for the reconstructions should be reasonable. The method used is based on high-order finite elements, parallel preconditioners from the Domain Decomposition method and Domain Specific Language with open source FreeFEM++ solver

Whole-microwave system modeling for brain imaging

In this paper, we present the results of a whole-system modeling of a microwave measurement prototype for brain imaging, consisting of 160 ceramic-loaded antennas working around 1 GHz. The modelization has been performed using open source FreeFem++ solver. Quantitative comparisons were performed using commercial software Ansys-HFSS and measurements. Coupling effects between antennas are studied with the empty system (without phantom) and simulations have been carried out with a fine numerical brain phantom model issued from scanner and MRI data for determining the sensitivity of the system in realistic configurations

Problèmes inverses et simulations numériques en viscoélasticité 3D.

In this thesis, we considered various mathematical and numerical problems related to the system of viscoelasticity in three dimensions. In the first part, we focused on the linear system and more specifically on the inverse problem of recovering a viscoelastic coefficient. For this system, we proved a Carleman estimate (Chapter 1) and a stability result in the unique continuation (Chapter 2). We used these results to establish two stability estimates for the inverse problem, the first one related to a unique internal measurement and the second to a unique measurement on an arbitrarily small part of the boundary (Chapter 3). Finally, we proposed a method to solve the problem numerically and presented an application in medical imaging (Chapter 4). In the second part, we studied a nonlinear viscoelasticity system. We presented numerical methods to solve it and the implementation of these methods in three dimensions (Chapter 5). A biomedical application to the simulation of the brain shift was then considered (Chapter 6). Finally, we looked at some modelling issues by establishing a viscoelastic/viscoplastic model in large strains (Chapter 7).Dans cette thèse, nous abordons plusieurs problèmes mathématiques et numériques relatifs aux équations de la viscoélasticité en trois dimensions. Dans la première partie, nous considérons le système linéaire et nous nous intéressons au problème inverse de récupération d'un coefficient viscoélastique. Pour ce système, nous démontrons une inégalité de Carleman (Chapitre 1) et un résultat de stabilité dans le prolongement unique (Chapitre 2). Nous utilisons ensuite ces résultats pour prouver deux inégalités de stabilité pour le problème inverse, l'une relative à une unique mesure interne et l'autre à une unique mesure sur une partie arbitrairement petite de la frontière (Chapitre 3). Finalement, nous proposons une méthode pour résoudre ce problème numériquement et présentons une application en imagerie médicale (Chapitre 4). Dans la deuxième partie, nous étudions le système de la viscoélasticité non linéaire. Nous présentons des méthodes numériques pour le résoudre et l'implémentation de ces dernières en trois dimensions sur des géométries complexes (Chapitre 5). Une application biomédicale à la simulation des déformations des structures cérébrales est ensuite décrite (Chapitre 6). Enfin, nous abordons une question de modélisation en proposant un modèle couplé viscoélastique/viscoplastique en grandes déformations (Chapitre7)

Logarithmic stability in determination of a 3D viscoelastic coefficient and a numerical example

International audienceWe prove a Carleman estimate and a logarithmic stability estimate for an inverse problem in three dimensional viscoelasticity. More precisely, we obtain logarithmic stability for the inverse problem of recovering the spatial part of a viscoelastic coefficient of the form p(x)h(t) from a unique measurement on an arbitrary part of the boundary. The main assumptions are: h (0) = 0, h(0) = 0, p is known in a neighborhood of the boundary and regularity and sensitivity of the reference trajectory. We propose a method to solve the problem numerically and illustrate the theoretical result by a numerical example

A new approach to solve the inverse scattering problem for waves: combining the TRAC and the Adaptive Inversion methods

The aim of this paper is to propose a new method to solve the inverse scattering problem. This method works directly in the time-dependent domain, using the wave equation and proceeds in two steps. The first step is the time-reversed absorbing condition (TRAC) method to reconstruct and regularize the signal and to reduce the computational domain. The second step is the adaptive inversion method to solve the inverse problem from the TRAC data, by using basis and mesh adaptation. This strategy allows us to recover the position, the shape and the properties of the scatterer in a precise and robust manner

Numerical resolution of an electromagnetic inverse medium problem at fixed frequency

International audienceThe aim of this paper is to solve numerically the inverse problem of determining the complex refractive index of an electromagnetic medium from partial boundary field measurements at a fixed frequency. The governing equations are the time-harmonic Maxwell equations formulated in electric field in a two-dimensional bounded domain. We express the inverse problem as the minimization of a cost function representing the difference between the measured and predicted fields. Our numerical reconstruction algorithm combines the BFGS method and an iterative process, called the Adaptive Eigenspace Inversion. The unknown complex coefficient is expanded in terms of eigenfunctions of an elliptic operator. Both the eigenspace and the mesh are iteratively adapted during the minimization procedure. Numerical experiments illustrate the performance of the reconstruction for various configurations