  The optimization of porous infill structures via local volume constraints has
become a popular approach in topology optimization. In some design settings,
however, the iterative optimization process converges only slowly, or not at
all even after several hundreds or thousands of iterations. This leads to
regions in which a distinct binary design is difficult to achieve. Interpreting
intermediate density values by applying a threshold results in large solid or
void regions, leading to sub-optimal structures. We find that this convergence
issue relates to the topology of the stress tensor field that is simulated when
applying the same external forces on the solid design domain. In particular,
low convergence is observed in regions around so-called trisector degenerate
points. Based on this observation, we propose an automatic initialization
process that prescribes the topological skeleton of the stress field into the
material field as solid simulation elements. These elements guide the material
deposition around the degenerate points, but can also be remodelled or removed
during the optimization. We demonstrate significantly improved convergence
rates in a number of use cases with complex stress topologies. The improved
convergence is demonstrated for infill optimization under homogeneous as well
as spatially varying local volume constraints.
