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Towards Predictive Models of Mechanical Properties in 3D-Printed Polymers: An Exploratory Study
* 1, 2 , * 1, 2 , 1
1  proMetheus, Higher School of Technology and Management, Polytechnic Institute of Viana do Castelo (IPVC), Viana do Castelo, Portugal.
2  Centre for Mechanical Technology and Automation (TEMA), Department of Mechanical Engineering, Universidade de Aveiro, Aveiro, Portugal.
Academic Editor: André Furtado

Abstract:

Additive manufacturing, particularly 3D printing, is increasingly shaping the production of polymer-based components, enabling complex geometries and tailored functional performance. Yet, predicting their mechanical behavior remains challenging due to material anisotropy and sensitivity to processing conditions. This work presents an exploratory study designed to provide the experimental basis for the development and calibration of predictive models of mechanical properties in 3D-printed components.

Standard ISO 527-2 Type 1A specimens were fabricated using two thermoplastics, PLA (polylactic acid) and ABS (acrylonitrile butadiene styrene), with systematic variations in layer orientation, infill overlap, and printing velocity. Mechanical characterization was carried out through uniaxial tensile testing to determine tensile strength and elastic modulus of the material specimens, while scanning electron microscopy (SEM) provided complementary insights into interlayer bonding, filament alignment, porosity, and fracture morphology.

Results showed that both material type and processing strategies strongly influenced mechanical response, with SEM highlighting microstructural features that govern interlayer adhesion and failure mechanisms. These findings contribute to a deeper understanding of process–structure–property relationships in additive manufacturing and establish the groundwork for predictive model development. Ongoing efforts will integrate these experimental insights into numerical simulations employing anisotropic and homogenized material models, thereby enhancing design optimization and reliability of 3D-printed structural components

Keywords: 3D printing; additive manufacturing; mechanical properties; predictive modeling; process–structure–property relationships.
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