Fabien Caubet

DETECTING AN OBSTACLE IMMERSED IN A FLUID BY SHAPE OPTIMIZATION METHODS

The paper presents a theoretical study of an identification problem by shape optimization methods. The question is to detect an object immersed in a fluid. Here, the problem is modeled by the Stokes equations and treated as a nonlinear least-squares problem. We consider both the Dirichlet and Neumann boundary conditions. Firstly, we prove an identifiability result. Secondly, we prove the existence of the first-order shape derivatives of the state, we characterize them and deduce the gradient of the least-squares functional. Moreover, we study the stability of this setting. We prove the existence of the second-order shape derivatives and we give the expression of the shape Hessian. Finally, the compactness of the Riesz operator corresponding to this shape Hessian is shown and the ill-posedness of the identification problem follows. This explains the need of regularization to numerically solve this problem.

Localization of small obstacles in Stokes flow

We want to detect small obstacles immersed in a fluid flowing in a larger bounded domain Ω in the three-dimensional case. We assume that the fluid motion is governed by the steady-state Stokes equations. We make a measurement on a part of the exterior boundary ∂Ω and then take a Kohn–Vogelius approach to locate these obstacles. We use here the notion of the topological derivative in order to determine the number of objects and their rough locations. Thus we first establish an asymptotic expansion of the solution of the Stokes equations in Ω when we add small obstacles inside. Then, we use it to find a topological asymptotic expansion of the considered Kohn–Vogelius functional which gives us the formula of its topological gradient. Finally, we make some numerical simulations exploring the efficiency and the limits of this method.

Instability of an Inverse Problem for the Stationary Navier--Stokes Equations

This paper provides a theoretical study of the detection of an object immersed in a fluid when the fluid motion is governed by the stationary Navier--Stokes equations with nonhomogeneous Dirichlet boundary conditions. To solve this inverse problem, we make a boundary measurement on a part of the exterior boundary. First, we present an identifiability result. We then use a shape optimization method: in order to identify the obstacle, we minimize a nonlinear least squares. Thus, we prove the existence of the first order shape derivative of the state, characterize it, and deduce the gradient of the least squares functional. Finally, we study the stability of this setting doing a shape sensitivity analysis of order two. Hence, we prove the existence of the second order shape derivatives and we give the expression of the shape Hessian at possible solutions of the original inverse problem. Then, the compactness of the Riesz operator corresponding to this shape Hessian is shown and the ill-posedness of the ident...

Shape optimization methods for the inverse obstacle problem with generalized impedance boundary conditions

We aim to reconstruct an inclusion ω immersed in a perfect fluid flowing in a larger bounded domain Ω via boundary measurements on ∂Ω. The obstacle ω is assumed to have a thin layer and is then modeled using generalized boundary conditions (precisely Ventcel boundary conditions). We first obtain an identifiability result (i.e. the uniqueness of the solution of the inverse problem) for annular configurations through explicit computations. Then, this inverse problem of reconstructing ω is studied, thanks to the tools of shape optimization by minimizing a least-squares-type cost functional. We prove the existence of the shape derivatives with respect to the domain ω and characterize the gradient of this cost functional in order to make a numerical resolution. We also characterize the shape Hessian and prove that this inverse obstacle problem is unstable in the following sense: the functional is degenerate for highly oscillating perturbations. Finally, we present some numerical simulations in order to confirm and extend our theoretical results.

Optimal location of resources for biased movement of species: the 1D case

In this paper, we investigate an optimal design problem motivated by some issues arising in population dynamics. In a nutshell, we aim at determining the optimal shape of a region occupied by resources for maximizing the survival ability of a species in a given box and we consider the general case of Robin boundary conditions on its boundary. Mathematically, this issue can be modeled with the help of an extremal indefinite weight linear eigenvalue problem. The optimal spatial arrangement is obtained by minimizing the positive principal eigenvalue with respect to the weight, under a L 1 constraint standing for limitation of the total amount of resources. The specificity of such a problem rests upon the presence of nonlinear functions of the weight both in the numerator and denominator of the Rayleigh quotient. By using adapted symmetrization procedures, a well-chosen change of variable, as well as necessary optimality conditions, we completely solve this optimization problem in the unidimensional case by showing first that every minimizer is unimodal and bang-bang. This leads to investigate a finite dimensional optimization problem. This allows to show in particular that every minimizer is (up to additive constants) the characteristic function of three possible domains: an interval that sticks on the boundary of the box, an interval that is symmetrically located at the middle of the box, or, for a precise value of the Robin coefficient, all intervals of a given fixed length.