  Skin modeling is an ongoing research area that highly benefits from modern
parallel algorithms. This article aims at applying shape optimization to
compute cell size and arrangement for elastic energy minimization of a cellular
composite material model for the upper layer of the human skin. A
gradient-penalized shape optimization algorithm is employed and tested on the
distributed-memory cluster Hazel Hen, HLRS, Germany. The performance of the
algorithm is studied in two benchmark tests. First, cell structures are
optimized with respect to purely geometric aspects. The model is then extended
such that the composite is optimized to withstand applied deformations. In both
settings, the algorithm is investigated in terms of weak and strong
scalability. The results for the geometric test reflect Kelvin's conjecture
that the optimal space-filling design of cells with minimal surface is given by
tetrakaidecahedrons. The PDE-constrained test case is chosen in order to
demonstrate the influence of the deformation gradient penalization on fine
inter-cellular channels in the composite and its influence on the multigrid
convergence. A scaling study is presented for up to 12,288 cores and 3 billion
DoFs.
