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Polymer Testing
Article . 2024 . Peer-reviewed
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A novel geometric predictive algorithm for assessing compressive elastic modulus in MEX additive processes, based on part nonlinearities and layers stiffness, validated with PETG and PLA materials

Authors: Jorge Manuel Mercado–Colmenero; Cristina Martin–Doñate;

A novel geometric predictive algorithm for assessing compressive elastic modulus in MEX additive processes, based on part nonlinearities and layers stiffness, validated with PETG and PLA materials

Abstract

The paper presents an innovative methodology based on the use of a new predictive algorithm created by the researchers capable of obtaining the elastic modulus of a plastic material manufactured with MEX and its mechanical behaviour in the elastic zone under compressive loads. The predictive algorithm only needs as input the compressive elastic modulus of the isotropic plastic material filament and the manufacturing parameters of the MEX process. The smart developed algorithm calculates the stiffness of each layer considering the number of holes in the projected area. The innovative predictive algorithm has been experimentally and numerically validated using PETG Polyethylene Terephthalate Glycol material and PLA Polylactic Acid on test specimens and on a case study of variable topology. The predictive algorithm is valid for each print pattern and manufacturing direction. The new algorithm improves the existing state of the art significantly since this algorithm extends its utility to most plastic polymer materials suitable for MEX 3D printing, provided that the mechanical and elastic properties of the filament are known. Its versatility extends to complex component geometries subjected to uniaxial compression loads, eliminating the need for mechanical analysis software or expensive experimental validations.

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Keywords

670, Material extrusion, Industrial design, 6, Computational Engineering, Finance, and Science, Predictive algorithms, Numerical simulations, CAD, 620

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average