  Process-induced defects are the leading cause of discrepancies between
as-designed and as-manufactured additive manufacturing (AM) product behavior.
Especially for metal lattices, the variations in the printed geometry cannot be
neglected. Therefore, the evaluation of the influence of microstructural
variability on their mechanical behavior is crucial for the quality assessment
of the produced structures. Commonly, the as-manufactured geometry can be
obtained by computed tomography (CT). However, to incorporate all
process-induced defects into the numerical analysis is often computationally
demanding. Thus, commonly this task is limited to a predefined set of
considered variations, such as strut size or strut diameter. In this work, a
CT-based binary random field is proposed to generate statistically equivalent
geometries of periodic metal lattices. The proposed random field model in
combination with the Finite Cell Method (FCM), an immersed boundary method,
allows to efficiently evaluate the influence of the underlying microstructure
on the variability of the mechanical behavior of AM products. Numerical
analysis of two lattices manufactured at different scales shows an excellent
agreement with experimental data. Furthermore, it provides a unique insight
into the effects of the process on the occurring geometrical variations and
final mechanical behavior.
