Computation of thickness and mechanical properties of interconnected structures: Accuracy, deviations and approaches for correction

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