  Randomness in the void distribution within a ductile metal complicates
quantitative modeling of damage following the void growth to coalescence
failure process. Though the sequence of micro-mechanisms leading to ductile
failure is known from unit cell models, often based on assumptions of a regular
distribution of voids, the effect of randomness remains a challenge. In the
present work, mesoscale unit cell models, each containing an ensemble of four
voids of equal size that are randomly distributed, are used to find statistical
effects on the yield surface of the homogenized material. A yield locus is
found based on a mean yield surface and a standard deviation of yield points
obtained from 15 realizations of the four-void unit cells. It is found that the
classical GTN model very closely agrees with the mean of the yield points
extracted from the unit cell calculations with random void distributions, while
the standard deviation $\textbf{S}$ varies with the imposed stress state. It is
shown that the standard deviation is nearly zero for stress triaxialities
$T\leq1/3$, while it rapidly increases for triaxialities above $T\approx 1$,
reaching maximum values of about $\textbf{S}/\sigma_0\approx0.1$ at $T \approx
4$. At even higher triaxialities it decreases slightly. The results indicate
that the dependence of the standard deviation on the stress state follows from
variations in the deformation mechanism since a well-correlated variation is
found for the volume fraction of the unit cell that deforms plastically at
yield. Thus, the random void distribution activates different complex
localization mechanisms at high stress triaxialities that differ from the
ligament thinning mechanism forming the basis for the classical GTN model. A
method for introducing the effect of randomness into the GTN continuum model is
presented, and an excellent comparison to the unit cell yield locus is
achieved.
