I'm trying to understand the notions of Euler and Hadamard derivatives of shape functionals. All the lecture notes and papers on this topic that I've found seem to build up on the books Shapes and Geometries and Introduction to Shape Optimization, which are both co-authored by Zolésio.
I've got a hard time trying to understand what they are doing. And if I'm not totally wrong (which is not unlikely) many things they are claiming don't make sense.
The basic idea should be to consider what happens to shape functions under an infinitesimal perturbation of the shape. So, it make sense to consider families $(T_t)_t$ of transformations $T_t$. But here starts the pain. The following excerpt is taken from section 2.9 of Introduction to Shape Optimization:
I don't even know where to start:
- I heavily doubt that the conclusion in the line immediately below (2.74) is correct (and it's weird that they use $C([0,\epsilon))$ on the rhs of (2.74), since this is usually a space of real-valued functions)
- How can (2.75) be well-defined if $t\mapsto T_t(x)$ is not even assumed to be differentiable for fixed $x$?
- And even if we assume that both $t\mapsto T_t(x)$ and $t\mapsto T_t^{-1}(x)$ are $C^1$-differentiable (which they do in a few sections before), I don't think that we can conclude (2.76); neither as stated with $C(0,\epsilon,C^k(\overline D,\mathbb R^N)$ nor with $C^1(0,\epsilon,C^k(\overline D,\mathbb R^N)$ as they seem to assume later on.
Now let's take a look at the definition of the Euler derivative:
I don't know what the space $\mathcal D(\mathbb R^N,\mathbb R^N)$ is, since they haven't defined this space at any point. From the notation it seems to be a space of distributions, but from its usage this doesn't seem to be the case. It's not clear to me how their notion of "shape differentiable in direction $V$" depends on $k$ and I actually don't even understand why we need $V\in C(0,\epsilon;V^k(D))$. In fact, it should be sufficient to assume that $T_t$ is any family of $C^1$-diffeomorphisms on $\mathbb R^N$ for $t\in[0,\epsilon)$ with $T_0=\operatorname{id}_{\mathbb R^N}$, $[0,\tau)\ni t\mapsto T_t(x)$ is differentiable for $x\in\mathbb R^N$ and $V_t:=\frac\partial{\partial t}T_t\circ T_t^{-1}$ for $t\in[0,\tau)$.
I guess, in analogy to the Fréchet derivative on Banach spaces, one wants to obtain a bounded linear operator $V\mapsto{\rm d}J(\Omega;V)$ and that's why we need to take $V$ from a suitable function spaces. I've seen other sources taking $V$ from some kind of Lipschitz functions or to be independent of time and from some Sobolev space. I'm really lost at this point by these apparently conflicting definitions.
Is there any better reference on this topic? I don't want to dive to deep into this stuff. It's sufficient to me to have rigorous treatment of basic shape functionals given by basic domain and boundary integrals which may or may not depend on the shape itself.