Effect of additive manufactured hybrid and functionally graded novel designed cellular lattice structures on mechanical and failure properties

Hussain, Sajjad; Nazir, Aamer; Waqar, Saad; Ali, Usman; Gokcekaya, Ozkan

doi:10.1007/s00170-023-12201-7

Cited by 10 publications

(2 citation statements)

References 44 publications

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“…One of the most promising applications of AM is the fabrication of lattice structures characterized by their periodic cellular architecture. These structures exhibit exceptional strength-to-weight ratios and adaptable mechanical properties, making them highly relevant across various domains, from aerospace applications to biomedical implantation [7,8]. The TPMS lattice structures represent an intricate and fascinating subset within the realm of lattice design.…”

Section: Introductionmentioning

confidence: 99%

A machine learning-based recommendation framework for material extrusion fabricated triply periodic minimal surface lattice structures

Hussain,

Lee,

Tsang

et al. 2024

Preprint

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Triply Periodic Minimal Surface (TPMS) lattice structures are utilized in diverse fields such as engineering, material design, and biomedical. The use of appropriate TPMS lattice structures in 3D printing can obtain benefits in terms of production efficiency and material reduction towards a greener 3D printing process. However, there is a lack of an automated solution to suggest the appropriate TPMS lattice structure parameters, such that unnecessary material wastage cannot be neglected in the existing practices. To address the above challenges, this study proposes a machine learning-based recommendation framework for generating the TPMS lattice structures based on the engineering requirements. First, we compiled a dataset by producing 144 samples via the material extrusion (ME) technique and conducted compression tests on four TPMS lattice structures (Diamond, Gyroid, Schwarz, and split-P), each with varying parameters, fabricated using Polylactic acid (PLA) material. Second, we train four machine learning algorithms (K-Nearest Neighbors, Decision Tree, Random Forest, and Bayesian Regression) on this dataset to predict TPMS lattice structure (unit cell type, unit cell size, and wall thickness). Extensive experiments assess algorithm performance using R-squared values and Root Mean Square Error (RMSE) as evaluation measures. Our results indicate that the Random Forest and Decision Tree algorithms perform best, achieving R-squared scores of 0.9694 and 0.9689, along with RMSE values of 0.1180 and 0.0795, respectively. This work not only advances the field's understanding of automated selection for TPMS lattice structures but also holds noteworthy implications for eco-design and eco-innovation, particularly in the realm of sustainable and efficient green 3D printing applications.

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Section: Introductionmentioning

confidence: 99%

A machine learning-based recommendation framework for material extrusion fabricated triply periodic minimal surface lattice structures

Hussain,

Lee,

Tsang

et al. 2024

Preprint

Self Cite

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“…Lattice structures-especially the Gyroid TPMS lattice, which is based on the triply periodic minimal surface (TPMS)-are becoming more and more popular in fields like biomedical, aerospace, and automotive engineering. This is due to their remarkable mechanical characteristics and adaptability [1][2][3][4][5][6] enhancing both shape and function, the bio-inspired Gyroid TPMS lattice draws its design ideas from nature, such as insect wings [7][8][9][10][11]. These lattices are perfect for distributing stresses and absorbing energy, which are essential for creating robust yet lightweight solutions.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Energy Absorption in Bioinspired Combined TPMS-Gyroid and Walled TPMS-Gyroid Lattice Structure Manufactured via Fused Filament Fabrication (FFF)

Alemayehu,

Todoh

2024

Preprint

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Bio-inspired gyroid triply periodic minimum surface (TPMS) lattice structures have been the focus of research in automotive engineering because they can absorb a lot of energy and have wider plateau ranges. The main challenge is determining the optimal energy absorption capacity and accurately capturing plastic plateau areas using finite element analysis (FEA). Using nTop's Boolean subtraction method, this study combined walled TPMS gyroid structures with normal TPMS gyroid lattice. This made a composite TPMS-gyroid lattice with relative densities ranging from 14% to 54%. Using the ideaMaker software and the fused deposition modeling (FDM) Raise3D Pro 2 3D printer to print polylactic acid (PLA) bioplastics in 1.75 mm filament made it possible to slice computer aided design (CAD) models and fabricate 36 lattices samples precisely layer by layer technique. Shimadzu 100kN testing equipment was utilized for the mechanical compression experiments. And the validation using finite element analysis (FEA). Further, CTG was examined using a field emission scanning electron microscope (FE-SEM) before and after compression testing. The composite TPMS gyroid lattice showed potential as shock absorbers for vehicles with relative densities of 33%, 38%, and 54%. The Gibson-Ashby model showed that the composite TPMS gyroid lattice deformed mainly by bending, and the size effect was seen when the relative densities were less than 15%. The lattice's relative density had a significant impact on its ability to absorb energy. The research also explored the use of these innovative foam-like composite TPMS-gyroid lattices in high-speed crash box scenarios, potentially enhancing vehicle safety and performance.

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Unveiling additively manufactured cellular structures in hip implants: a comprehensive review

Dias,

da Silva,

Gasik

et al. 2023

Int J Adv Manuf Technol

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The prospect of improved quality of life and the increasingly younger age of patients benefiting from Total Hip Arthroplasty will soon lead to the landmark of 10 million interventions per year worldwide. More than 10% of these procedures lead to significant bone resorption, increasing the need for revision surgeries. Current research focuses on the development of hip implant designs to achieve a stiffness profile closer to the natural bone. Additive Manufacturing has emerged as a viable solution by offering promising results in the fabrication of implant architectures based on metallic cellular structures that have demonstrated their capacity to replicate bone behavior mechanically and biologically. Aiming to offer an up-to-date overview of titanium cellular structures in hip implants, for both acetabular and femoral components, produced by Additive Manufacturing, including its design intricacies and performance, this comprehensive review meticulously examines the historical development of hip implants, encompassing commercial solutions and innovative attempts. A broad view of the practical applications and transformative potential of hip implants incorporating cellular structures is presented, aiming to outline opportunities for innovation.

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Effect of additive manufactured hybrid and functionally graded novel designed cellular lattice structures on mechanical and failure properties

Cited by 10 publications

References 44 publications

A machine learning-based recommendation framework for material extrusion fabricated triply periodic minimal surface lattice structures

A machine learning-based recommendation framework for material extrusion fabricated triply periodic minimal surface lattice structures

Enhanced Energy Absorption in Bioinspired Combined TPMS-Gyroid and Walled TPMS-Gyroid Lattice Structure Manufactured via Fused Filament Fabrication (FFF)

Unveiling additively manufactured cellular structures in hip implants: a comprehensive review

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