Necessary conditions for the optimal control of a shape optimization problem with non-smooth PDE constraints

TL;DR

This paper derives necessary optimality conditions for shape optimization problems governed by non-smooth PDEs, addressing challenges due to non-differentiability and unknown domains.

Contribution

It introduces a novel approach to obtain first-order necessary conditions for non-smooth PDE-constrained shape optimization problems, including boundary measures and Clarke subdifferential inclusion.

Findings

Derived an adjoint equation for the non-smooth problem

Established a limit gradient equation with boundary measure

Formulated an inclusion involving Clarke subdifferential

Abstract

This paper is concerned with the derivation of necessary conditions for the optimal shape of a design problem governed by a non-smooth PDE. The main particularity thereof is the lack of differentiability of the nonlinearity in the state equation, which, at the same time, is solved on an unknown domain. We follow the functional variational approach introduced in [37] where the set of admissible shapes is parametrized by a large class of continuous mappings. It has been recently established [4] that each parametrization associated to an optimal shape is the limit of a sequence of global optima of minimization problems with convex admissible set consisting of functions. Though non-smooth, these problems allow for the derivation of an optimality system equivalent with the first order necessary optimality condition [5]. In the present manuscript we let the approximation parameter vanish therein. The final necessary conditions for the non-smooth shape optimization problem consist of an adjoint equation, a limit gradient equation that features a measure concentrated on the boundary of the optimal shape and, because of the non-smoothness, an inclusion that involves its Clarke subdifferential.