December 1 - 6, 2024
Boston, Massachusetts
Symposium Supporters
2024 MRS Fall Meeting & Exhibit
PM02.10.02

Optimizing Victoria Water Lily Inspired Lattices with Generative Design for Enhanced Strength and Tunable Directional Stiffness

When and Where

Dec 5, 2024
8:00pm - 10:00pm
Hynes, Level 1, Hall A

Presenter(s)

Co-Author(s)

Brennan Birn1,Kyle Woody1,Dominique Sun1,Grace Gu1

University of California, Berkeley1

Abstract

Brennan Birn1,Kyle Woody1,Dominique Sun1,Grace Gu1

University of California, Berkeley1
The Victoria Amazonica, also known as the Victoria Water Lily, is one of the most impressive plants in the rivers of the Amazon Rainforest. Its leaves grow up to 3 meters in size and can support up to 70 kg of weight. Previous studies noted the high stiffness of this structure when developing a tessellated unit cell inspired by the center structure of the water lily. Inspired by the lily pad, these studies developed a 3D structure of 9 beams and flipped the structure on itself to ensure vertical symmetry. This 3D structure outperforms many other bioinspired structures in the literature. Although this structure shows promise, it has yet to be optimized for the unidirectional compression it was designed for, and it has a nonideal stiffness matrix. Here, we show how the Victoria Water Lily lattice can achieve greater relative stiffness, strength, and isotropy when optimized using generative design. We found that optimizing the lily pad resulted in a substantial increase in stiffness with a more transversely isotropic stiffness matrix, ideal for unidirectional compression. Our results demonstrate that generative design tunes the stiffness distribution of bioinspired lattice structures while decreasing the overall anisotropy. We anticipate this will kickstart generative design for lattice structure optimization for various properties and applications due to the growing availability of generative design tools and the fact that generative design produces parts with a significantly smoother finish than other methods, such as topology optimization. It can, therefore, produce parts that are immediately ready for additive manufacturing and testing without the need for extensive user modification or an incredibly fine mesh.

Keywords

3D printing | metamaterial

Symposium Organizers

Grace Gu, University of California, Berkeley
Yu Jun Tan, National University of Singapore
Ryan Truby, Northwestern University
Daryl Yee, École Polytechnique Fédérale de Lausanne

Session Chairs

Grace Gu
Yu Jun Tan

In this Session