Digital Image Correlation and Finite Element Computation to Reveal Mechanical Anisotropy in 3D Printing of Polymers - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Journal Articles Materials Year : 2022

Digital Image Correlation and Finite Element Computation to Reveal Mechanical Anisotropy in 3D Printing of Polymers

Abstract

In this study, we propose to revisit the mechanical anisotropy inferred to printed ABS polymers using fused deposition modelling by combining digital image correlation (DIC), mechanical testing and finite element computation. Tensile specimens are printed using different design orientations and raster angles. Monitoring of deformed samples is performed, and strain fields are derived for each configuration. Finite element modelling of the 3D-printed material behaviour is considered to shed more light on deformation mechanisms. Experimental results show that a heterogeneous strain field develops, leading to more significant strain localisation for samples printed with the main dimension aligned with the building direction. The optimal printing angle allowing the filament to be crossed at −45°/+45° shows the best behaviour with even larger elongation at break compared to the raw material. However, digital image correlation based on optical imaging shows that a limiting scale exists for revealing the effect of filament orientation on strain localisation. Finite element results reveal the nature of the strain localisation as related presence of porosity close to the frame and the development of asymmetrical filling within the printed structure.
Fichier principal
Vignette du fichier
2022_Guessasma_Materials.pdf (13.93 Mo) Télécharger le fichier
Origin Publisher files allowed on an open archive
Licence

Dates and versions

hal-04132941 , version 1 (19-06-2023)

Licence

Identifiers

Cite

Sofiane Guessasma, Hedi Nouri, Sofiane Belhabib. Digital Image Correlation and Finite Element Computation to Reveal Mechanical Anisotropy in 3D Printing of Polymers. Materials, 2022, 15 (23), pp.8382. ⟨10.3390/ma15238382⟩. ⟨hal-04132941⟩
89 View
9 Download

Altmetric

Share

More