PSI - Issue 68

ScienceDirect Structural Integrity Procedia 00 (2025) 000–000 Structural Integrity Procedia 00 (2025) 000–000 Available online at www.sciencedirect.com Available online at www.sciencedirect.com ScienceDirect Available online at www.sciencedirect.com ScienceDirect

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Procedia Structural Integrity 68 (2025) 77–83

European Conference on Fracture 2024 Fatigue life prediction of ABS/Graphene nanoplatelets 3D-printed composite parts Soran Hassanifard a , Kamran Behdinan a, * European Conference on Fracture 2024 Fatigue life prediction of ABS/Graphene nanoplatelets 3D-printed composite parts Soran Hassanifard a , Kamran Behdinan a, * Abstract A computational model has been developed to predict the fatigue life of Acrylonitrile Butadiene Styrene (ABS)/Graphene Nanoplatelet (GNP) composite parts produced using Fused Filament Fabrication (FFF) technique. This model accounts for key factors such as raster angles, GNP content in the filaments, and material degradation during cyclic loading. Fatigue life predictions were performed using two strain-based models: the modified Morrow model and the Smith-Watson-Topper (SWT) model. To address the effects of internal defects in 3D-printed parts, the model employed an innovative approach, treating the defected parts as homogeneous, defect-free components but with an imaginary notch and associated notch strength reduction factors at various load levels. The results demonstrated that this method effectively predicts fatigue life of FFF-processed 3D-printed parts. © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of ECF24 organizers Keywords: additive manufacturing; ABS/graphene nanoplatelets; fatigue 1. Introduction Additive manufacturing (AM) has gained increasing popularity due to its ability to produce complex geometries across a broad range of scales, from nano to macro (Rogkas et al., 2022; Sola et al., 2023). This technology has been employed in the fabrication of highly sensitive components, such as rocket engine parts by NASA (Alami et al., 2023) and various biomedical applications (Kumar et al., 2021). However, challenges such as anisotropy, internal defects, © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of ECF24 organizers a Advanced Research Laboratory for Multifunctional Lightweight Structures (ARL-MLS), Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada a Advanced Research Laboratory for Multifunctional Lightweight Structures (ARL-MLS), Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada Abstract A computational model has been developed to predict the fatigue life of Acrylonitrile Butadiene Styrene (ABS)/Graphene Nanoplatelet (GNP) composite parts produced using Fused Filament Fabrication (FFF) technique. This model accounts for key factors such as raster angles, GNP content in the filaments, and material degradation during cyclic loading. Fatigue life predictions were performed using two strain-based models: the modified Morrow model and the Smith-Watson-Topper (SWT) model. To address the effects of internal defects in 3D-printed parts, the model employed an innovative approach, treating the defected parts as homogeneous, defect-free components but with an imaginary notch and associated notch strength reduction factors at various load levels. The results demonstrated that this method effectively predicts fatigue life of FFF-processed 3D-printed parts. © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of ECF24 organizers Keywords: additive manufacturing; ABS/graphene nanoplatelets; fatigue 1. Introduction Additive manufacturing (AM) has gained increasing popularity due to its ability to produce complex geometries across a broad range of scales, from nano to macro (Rogkas et al., 2022; Sola et al., 2023). This technology has been employed in the fabrication of highly sensitive components, such as rocket engine parts by NASA (Alami et al., 2023) and various biomedical applications (Kumar et al., 2021). However, challenges such as anisotropy, internal defects,

* Corresponding author. E-mail address: behdinan@mie.utoronto.ca * Corresponding author. E-mail address: behdinan@mie.utoronto.ca

2452-3216 © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of ECF24 organizers 2452-3216 © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of ECF24 organizers

2452-3216 © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of ECF24 organizers 10.1016/j.prostr.2025.06.025