Transactions on Additive Manufacturing Meets Medicine
Vol. 6 No. S1 (2024): Trans. AMMM Supplement
https://doi.org/10.18416/AMMM.2024.24091795%20

Imaging and Modelling in 3D Printing, ID 1795

Inverse multi-objective design of heterogeneous cellular structures

Main Article Content

Ramin Yousefi Nooraie (Department of Mechanical Engineering, Politecnico di Milano, Milano, Italy), Mario Guagliano (Department of Mechanical Engineering, Politecnico di Milano, Milano,), sara Bagherifard (Department of Mechanical Engineering, Politecnico di Milano, Milano,)

Abstract

Architected lattice structures, featuring multiple sub-elements arranged in deliberate patterns, can achieve a notably wider array of properties than their uniform counterparts. Traditional design methods for these materials typically depend on expert knowledge and require considerable trial and error effort.


Here, we introduce a data-efficient approach for optimizing 3D-printed architected structures combining two distinct unit cell topologies. This approach uses a framework pairing a Deep Neural Network (DNN) with a Genetic Algorithm (GA), supported by finite element method (FEM) simulations to inverse design heterogeneous lattice structures with tailored elastic modulus and energy absorption efficiency at a low weight.


We specifically apply this method to orthopedic implant design, as a case study to offer structures with biocompatible elastic modulus, and enhanced energy absorption efficiency. Our approach thus provides a data-efficient model for the rapid and intelligent design of architected materials with site-specific customized mechanical and physical properties with a high potential to be used for biomedical implants.

Article Details

How to Cite

Yousefi Nooraie, R., Guagliano, M., & Bagherifard, sara. (2024). Inverse multi-objective design of heterogeneous cellular structures . Transactions on Additive Manufacturing Meets Medicine, 6(S1), 1795 . https://doi.org/10.18416/AMMM.2024.24091795