jiayingqi/heterogeneous-virtual-growth

Generates patterns with seamlessly connected building blocks

Heterogeneous Virtual Growth Algorithm

This program generates patterns with seamlessly connected building blocks.

The program generalizes the virtual growth scheme to account for spatially varying frequency hints. It also converts the generated patterns to FEA meshes and evaluate their homogenized elasticity matrices.

Examples

2D pattern

3D pattern

2D FEA mesh (Q4 elements)

3D FEA mesh (frame elements)

How to use this program

Installation

To download the code, run the following command in your terminal:

git clone https://github.com/jiayingqi/Heterogeneous-Virtual-Growth

Then run the following command to install xvfb for visualization:

apt-get -qq update && apt-get -y install libgl1-mesa-dev xvfb

Finally, run the following command to install the required Python packages:

pip3 install -r requirements.txt

Start with the program

Generate the adjacency rules:

python3 scripts/generate_rules_script.py

Generate the patterns:

python3 scripts/virtual_growth_script.py

Convert the patterns to FEA meshes:

python3 scripts/generate_mesh_script.py

Evaluate the homogenized elasticity matrices:

python3 scripts/homogenize_script.py

Authors, sponsors, and citation

Authors

• Yingqi Jia ([email protected])
• Ke Liu ([email protected])
• Xiaojia Shelly Zhang ([email protected])

Sponsor

• David C. Crawford Faculty Scholar Award from the Department of Civil and Environmental Engineering and Grainger College of Engineering at the University of Illinois

Citations

• Jia, Y., Liu, K., Zhang, X.S., 2024. Modulate stress distribution with bio-inspired irregular architected materials towards optimal tissue support. Nature Communications 15, 4072. https://doi.org/10.1038/s41467-024-47831-2
• Jia, Y., Liu, K., Zhang, X.S., 2024. Topology optimization of irregular multiscale structures with tunable responses using a virtual growth rule. Computer Methods in Applied Mechanics and Engineering 425, 116864. https://doi.org/10.1016/j.cma.2024.116864