Classical laminate theory for flexural strength prediction of FDM 3D printed PLAs

Rajpurohit, SR, Dave, HK and Bodaghi, M ORCID logoORCID: https://orcid.org/0000-0002-0707-944X, 2023. Classical laminate theory for flexural strength prediction of FDM 3D printed PLAs. Materials Today: Proceedings. ISSN 2214-7853

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Abstract

Fused Deposition Modeling (FDM) is a prominent Additive Manufacturing (AM) technology for producing tailored components with complicated geometries, particularly from thermoplastics. Due to poor mechanical performance and printed component quality, this technology was limited in its capacity to make parts for industrial applications. As a result, researchers are being encouraged to improve the mechanical performance of FDM components in order to meet the huge demand for functional components. The selection of process variables has a considerable effect on the mechanical performance of FDM products. Therefore, the correlation between the mechanical properties and process variables should be evaluated. This paper highlights the flexural strength of the FDM parts at different raster orientation and describe the flexural strength through classical laminate theory (CLT). The elastic constant was derived for unidirectional (UD) UD0°, UD45°, and UD90° plies at various layer height and raster width combinations. The constitutive models were developed using experimentally derived elastic constant to calculate the flexural strength of the UD0°, UD45°, and UD90° parts and the results were validated against the experimental value. Furthermore, flexural strength was analyzed at various raster orientation for different combinations of layer height and raster width. Results show that experimentally measured flexural strength decreases with raster orientation and can be estimated by CLT model. The nature of failure under flexural loads was further investigated using fractography analysis of failure surfaces for FDM laminates.

Item Type: Journal article
Publication Title: Materials Today: Proceedings
Creators: Rajpurohit, S.R., Dave, H.K. and Bodaghi, M.
Publisher: Elsevier
Date: 25 March 2023
ISSN: 2214-7853
Identifiers:
Number
Type
10.1016/j.matpr.2023.03.310
DOI
S2214785323013561
Publisher Item Identifier
1751350
Other
Divisions: Schools > School of Science and Technology
Record created by: Jonathan Gallacher
Date Added: 09 May 2023 07:51
Last Modified: 25 Mar 2024 03:00
URI: https://irep.ntu.ac.uk/id/eprint/48892

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