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Lookup NU author(s): Dr Yao Chen, Dr Arti Yadav, Professor Steve BullORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2021, The Author(s). Although the literature is abundant with the experimental methods to characterize mechanical behavior of parts made by fused filament fabrication 3D printing, less attention has been paid in using computational models to predict the mechanical properties of these parts. In the present paper, a numerical homogenization technique is developed to predict the effect of printing process parameters on the elastic response of 3D printed parts with cellular lattice structures. The development of finite element computational models of printed parts is based on a multi scale approach. Initially, at the micro scale level, the analysis of micro-mechanical models of a representative volume element is used to calculate the effective orthotropic properties. The finite element models include different infill densities and building/raster orientation maintaining the bonded region between the adjacent fibers and layers. The elastic constants obtained by this method are then used as an input for the creation of macro scale finite element models enabling the simulation of the mechanical response of printed samples subjected to the bending, shear, and tensile loads. Finally, the results obtained by the homogenization technique are validated against more realistic finite element explicit microstructural models and experimental measurements. The results show that, providing an accurate characterization of the properties to be fed into the macro scale model, the use of the homogenization technique is a reliable tool to predict the elastic response of 3D printed parts. The outlined approach provides faster iterative design of 3D printed parts, contributing to reducing the number of experimental replicates and fabrication costs.
Author(s): Gonabadi H, Chen Y, Yadav A, Bull S
Publication type: Article
Publication status: Published
Journal: International Journal of Advanced Manufacturing Technology
Year: 2022
Volume: 118
Issue: 5-6
Pages: 1485-1510
Print publication date: 01/01/2022
Online publication date: 17/09/2021
Acceptance date: 21/08/2021
Date deposited: 06/07/2022
ISSN (print): 0268-3768
ISSN (electronic): 1433-3015
Publisher: Springer UK
URL: https://doi.org/10.1007/s00170-021-07940-4
DOI: 10.1007/s00170-021-07940-4
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