Experimental characterization of spatial variability for random field modeling on struts of additively manufactured lattice structures

Abstract

The accuracy of the numerical predictions of lattice structures relies on the quantification of the uncertainties introduced by additive manufacturing (AM). In this study, an efficient random field discretization framework is proposed to characterize the spatial variability of geometric uncertainties on the strut members of the lattice structures fabricated by a specific AM process called material extrusion. Individual struts are fabricated with various printing angles and diameters using PLA material. Diameter values of the fabricated samples are measured along the printing direction and the radial direction of the cross-section at each layer under an optical microscope. Spatial correlations are characterized based on the measurements and the correlation lengths are evaluated. Two random field discretization methods, namely Karhunen-Loève expansion (KLE) and Expansion Optimal Linear Estimation (EOLE) methods are investigated to reduce the dimensionality of the random field discretization. The KLE method was found to give better accuracy in terms of error means while EOLE can produce better local accuracy. An optimal mesh size determination approach is introduced for the random field discretization with the expansion methods based on the number of expansion terms. The voxel-based strut models are generated with the diameter parameters modeled by the proposed random fields discretization framework. The comparison of the generated models with the fabricated struts shows that the AM-introduced variability in the material extrusion process on the struts is well represented by the random field modeling technique.