| About this Abstract |
| Meeting |
2021 TMS Annual Meeting & Exhibition
|
| Symposium
|
Design and Manufacturing Approaches for the Next Generation of Sustainable Materials: The 2021 Student-led Symposium
|
| Presentation Title |
Challenges in Optimizing Structural Metamaterials |
| Author(s) |
Brad L. Boyce, Anthony Garland, Benjamin White, Ryan Alberdi |
| On-Site Speaker (Planned) |
Brad L. Boyce |
| Abstract Scope |
Lattice metamaterials have been shown to exhibit several beneficial properties, ranging from structural lightweighting to acoustic damping. Now, with the proliferation and maturation of additive manufacturing technologies, such structures are becoming more accessible and cost-effective. However, to best use metamaterials to their fullest extent, several challenges must still be addressed. During manufacturing, residual stress and warpage, location-dependent microstructure, orientation-dependent surface roughness and lack-of-fusion porosity all remain outstanding challenges. Design optimization methods rarely consider these manufacturability tradeoffs. Furthermore, existing topology optimization algorithms generally can only address linear problems such as elastic behavior, while nonlinear optimization of elastoplastic behavior and fracture resistance is only recently emerging. Finally, the computational expense of finite element representations for large-scale lattice structures requires innovative approaches, typically in the form of reduced order models. We will explore the use of convolutional neural networks, which provides one potential path to address several of these issues simultaneously. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Mechanical Properties, Other |