AbstractIdentifying local thickness information of fibrous or highly porous structures is challenging.
The analysis of tomography data calls for computationally fast, robust, and accurate
algorithms. This work systematically investigates systematic errors in the thickness
computation and the impact of observed deviations on the predicted mechanical
properties using a set of 16 model structures with varying ligament shape and solid
fraction. Strongly concave, cylindrical, and convex shaped ligaments organized in a
diamond structure are analyzed. The predicted macroscopic mechanical properties
represent a highly sensitive measure for systematic errors in the computed geometry.
Therefore, the quality of proposed correctionmethods is assessed via FEMbeammodels
that can be automatically generated from the measured data and allow an efficient
prediction of the mechanical properties. The results show that low voxel resolutions can
lead to an overprediction of up to 30% in the Young’s modulus. A model scanned with
a resolution of 200 voxels per unit cell edge (8M voxels) reaches an accuracy of a few
percent. Analyzing models of this resolution with the Euclidean distance transformation
showed an underprediction of up to 20% for highly concave shapes whereas cylindrical
and slightly convex shapes are determined at high accuracy. For the Thickness algorithm,
the Young’s modulus and yield strength are overpredicted by up to 100% for highly
concave ligament shapes. A proposed Smallest Ellipse approach corrects the Thickness
data and reduces this error to 20%. It can be used as input for a further robust
correction of the Thickness data using an artificial neural network. This approach is highly
accuratewith remnant errors in the predictedmechanical properties of only a few percent.
Furthermore, the data from the FEM beam models are compared to results from FEM
solidmodels providing deeper insights toward further developments on nodal corrections
for FEM beam models. As expected, the FEM beam models show an increasing
overprediction of the compliance with increasing solid fraction. As an unexpected result,
the mechanical strength can however be underpredicted or overpredicted, depending
on the ligament shape. Therefore, a nodal correction is needed that solves contradicting
tasks in terms of stiffness and strength.