About this Abstract |
Meeting |
2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
|
Symposium
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2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
|
Presentation Title |
A Data-driven Approach for Multi-Topology Lattice Transitions |
Author(s) |
Martha Baldwin, Nicholas A Meisel, Christopher McComb |
On-Site Speaker (Planned) |
Martha Baldwin |
Abstract Scope |
Additive manufacturing is advantageous for producing lightweight components while maintaining function and form. This ability has been bolstered by the introduction of unit lattice cells and the gradation of those cells. In cases where the loading varies throughout a part, it may be necessary to use multiple lattice cell types, also known as multi-topology lattice structures. In such structures, abrupt transitions between lattice types may cause stress concentrations, making the boundary a primary failure point; thus, transition regions should be created between each lattice cell type. However, smooth transition regions are currently difficult to intuit and design, especially between lattices of drastically different geometries. This work demonstrates and assesses a method for using variational autoencoders to automate the creation of transitional lattice cells. Such a data-driven approach has the potential to achieve complex unit cell transitions over varying transition lengths, promoting innovative solutions. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |