Prediction of tensile performance for 3D printed photopolymer gyroid lattices using structural porosity, base material properties, and machine learning

Prediction of tensile performance for 3D printed photopolymer gyroid lattices using structural porosity, base material properties, and machine learning

Advancements in additive manufacturing (AM) technology and three-dimensional (3D) modeling software have enabled the fabrication of parts with combinations of properties that were impossible to achieve with traditional manufacturing techniques. Porous designs such as truss-based and sheet-based latt...

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Bibliographic Details
Main Authors: Jacob Peloquin, Alina Kirillova, Cynthia Rudin, L.C. Brinson, Ken Gall
Format: Article
Language:English
Published: Elsevier 2023-08-01
Series:Materials & Design
Subjects:
Machine learning
Mechanical performance
Lattice structures
Diverse materials
Additive manufacturing
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127523005415

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http://www.sciencedirect.com/science/article/pii/S0264127523005415

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