On the assessment of the mechanical properties of additively manufactured lattice structures. (September 2022)

• Record Type: Journal Article
• Authors: Ali, Mubasher; Sajjad, Uzair; Hussain, Imtiyaz; Abbas, Naseem; Ali, Hafiz Muhammad; Yan, Wei-Mon; Wang, Chi-Chuan
• Is Part Of: Engineering analysis with boundary elements. Volume 142(2022)
• Page Start: 93
• Page End: 116
• Publication Date: 2022-09
• Subjects: Additive Manufacturing -- Artificial Intelligence -- Machine Learning -- Lattice Structure -- Mechanical Properties; Boundary element methods -- Periodicals; Engineering mathematics -- Periodicals; Équations intégrales de frontière, Méthodes des -- Périodiques; Mathématiques de l'ingénieur -- Périodiques; Boundary element methods; Engineering mathematics; Periodicals; 620.00151
• DOI: 10.1016/j.enganabound.2022.05.019
• Languages: English
• ISSNs: 0955-7997

Abstract

Abstract: Lattice structures fabricated by additive manufacturing (AM) technology have many excellent properties, such as lightweight, high strength, energy absorption, and vibration reduction, which have been extensively researched and made a breakthrough. Lattice structures have been commonly used in aviation, bioengineering, robotics, and other industrial fiber because of their outstanding properties. The first part of this article provides a short review on the assessment of mechanical properties of various lattice structures in terms of their classification, applications, materials and fabrication techniques, and complexity of designing, fabrication, and post-processing as well as some of the numerical models to predict the mechanical properties of the lattice structures. The second part of the article proposes a deep learning (DL) model for a highly accurate stress-strain behavior assessment of numerous lattice structures such as namely: the octet, face center-cubic, body-centered cubic, diamond, rhombic, cubic, truncated cube, and truncated cuboctahedron, etc, which were fabricated using many different materials via various approaches and methods. Using the proposed DL model, an accuracy in terms of R 2 = 0.999 (correlation coefficient), MSE = 0.0017 (mean squared error), and MAE = 0.0312 (mean absolute error) can be achieved for the prediction of the deemed mechanical property of the lattice structures. The model contains simple, quick and precise predictability that makes it ideal for the use of lattice structures in various practical applications, including heater and heat exchangers, engine hood, biomedical implant, wings, gas turbine, vibration absorber, robotic device, etc.