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Article Dans Une Revue Applied Mathematics and Optimization Année : 2022

Shape sensitivity of eigenvalue functionals for scalar problems: computing the semi-derivative of a minimum

Résumé

This paper is devoted to the computation of certain directional semi-derivatives of eigenvalue functionals of self-adjoint elliptic operators involving a variety of boundary conditions. A uniform treatment of these problems is possible by considering them as a problem of calculating the semi-derivative of a minimum with respect to a parameter. The applicability of this approach, which can be traced back to the works of Danskin and Zolésio, to the treatment of eigenvalue problems (where the full shape derivative may not exist, due to multiplicity issues), has been illustrated by Zolésio. Despite this, some of the recent literature on the shape sensitivity of eigenvalue problems still continue to employ methods such as the material derivative method or Lagrangian methods which seem less adapted to this class of problems. The Delfour-Zolésio approach does not seem to be fully exploited in the existing literature: we aim to recall the importance and the simplicity of these ideas, by applying it to the analysis of the shape sensitivity for eigenvalue functionals for a class of elliptic operators in the scalar setting (Laplacian or diffusion in heterogeneous media), thus recovering known results in the case of Dirichlet or Neumann boundary conditions and obtaining new results in the case of Steklov or Wentzell boundary conditions.
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Dates et versions

hal-02511124 , version 1 (18-03-2020)
hal-02511124 , version 2 (28-02-2022)

Identifiants

Citer

Fabien Caubet, Marc Dambrine, Rajesh Mahadevan. Shape sensitivity of eigenvalue functionals for scalar problems: computing the semi-derivative of a minimum. Applied Mathematics and Optimization, In press, 86 (1), pp.10. ⟨10.1007/s00245-022-09827-6⟩. ⟨hal-02511124v2⟩
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