A novel way of computing the shape derivative for a class of non-smooth PDEs and its impact on deriving necessary conditions for locally optimal shapes

We derive necessary conditions for locally optimal shapes of a design problem governed by a non-smooth PDE. The main particularity of the state system is the lack of differentiability of the nonlinearity. We work in the framework of the functional variational approach (FVA), which has the capacity to transfer geometric optimization problems into optimal control problems, the set of admissible shapes being parametrized by a large class of continuous mappings. In the FVA setting, we introduce a sensitivity analysis technique that is novel even for smooth PDEs. We emphasize that we do not resort to extensions on the hold-all domain or any kind of approximation of the original PDE. The computation of the directional derivative of the state w.r.t. functional variations results in a new way of computing the shape derivative. The presented approach allows us to handle in the objective pointwise observation and derivatives of the state on an observation set as well as distributed observation terms. In addition, we introduce the concept of locally optimal shapes and we put into evidence its connection to locally minimizers of the corresponding control problem. With directional differentiability results for the control-to-state map at our disposal, we can then state necessary conditions for locally optimal shapes in general non-smooth settings.