Gyroid Permeability Modeling With Python and 3D Prints

ISEF Category: Engineering Technology: Statics and Dynamics

Subcategory: Computational Mechanics  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

A tiny change in pore shape can flip how fast water moves through a material. That matters for filters, bone scaffolds, heat exchangers, and lightweight parts. In this project, you test whether a Python flow model can predict what a real 3D-printed gyroid does. You also learn how engineers compare simulation to messy physical data.

What Is It?

A gyroid is a repeating 3D shape that looks like a twisted maze. It has open channels, so fluid can pass through it. When you change porosity, the amount of empty space in the structure, you change how easily water flows through the sample.

Your project asks whether a lattice-Boltzmann solver, a fluid simulation method that tracks how fluid particles move on a grid, can estimate permeability. Permeability means how easily a porous material lets fluid pass. Think of it like the difference between pouring water through pebbles versus through a sponge. The pebbles block flow. The sponge gives water connected paths.

Why This Is a Good Topic

This topic works well because you can test a real engineering question with both code and hardware. You have a clear independent variable, porosity, and a clear output, permeability. That makes the project measurable and easy to compare across samples. It also connects to real design problems in filtration, biomedical implants, and thermal management, so your results have a practical use.

Research Questions

• How does porosity change the permeability of 3D-printed gyroid samples??
• How does gyroid unit-cell size affect the gap between simulated and measured permeability??
• What is the effect of print orientation on Darcy-flow measurements in gyroid lattices??
• To what extent does the lattice-Boltzmann prediction match a column-of-water Darcy rig across porosity levels??
• Which boundary condition choice in the Python solver gives permeability estimates closest to experimental data??
• How does sample thickness change the measured pressure drop for the same gyroid geometry??

Basic Materials

• 3D printer or access to a school maker space with a resin or filament printer.
• CAD software for creating gyroid geometries.
• Digital calipers.
• Kitchen or digital scale with at least 0.1 g resolution.
• Clear tubing and connectors for a simple water-flow rig.
• Graduated cylinder or measuring cup.
• Stopper or clamp system to hold the sample in place.
• Waterproof container or sink-safe setup.
• Spreadsheet software for data logging.
• Computer that can run Python.

Advanced Materials

• Access to a higher-resolution 3D printer.
• Pressure sensors or a differential manometer.
• Flow meter or precision balance for flow-rate measurement.
• Scanning software or micro-CT access for geometry verification.
• Python scientific stack for simulation and analysis.
• Access to a materials or fluids lab for controlled permeability testing.
• Image analysis software for measuring print defects and pore variation.
• Temperature probe for tracking fluid-property changes.

Software & Tools

• Python: Runs the lattice-Boltzmann solver, data cleaning, and comparison plots.
• NumPy: Handles arrays for grid-based flow calculations and geometry masks.
• Matplotlib: Makes permeability, pressure-drop, and error graphs.
• ImageJ: Measures printed pore dimensions and checks geometry from photos or scans.
• CAD software: Builds the gyroid samples and exports printable files.

Experiment Steps

1. Define one geometry variable first, such as porosity, unit-cell size, or wall thickness.
2. Build a digital gyroid model that you can print in several controlled versions.
3. Plan a flow test that turns water movement into a permeability value using the same sample holder each time.
4. Set up a Python simulation that matches the same geometry and boundary conditions as the physical test.
5. Decide how you will compare simulation output to experiment with error metrics, not just visual matches.
6. Design repeat runs and control samples so you can tell geometry effects from print defects and measurement noise.

Common Pitfalls

• Printing gyroids with clogged or inconsistent pores, which changes the actual porosity away from the CAD design.
• Letting the sample leak around the edges of the holder, which makes the Darcy test measure bypass flow instead of flow through the lattice.
• Comparing simulation to experiment without matching the same boundary conditions, which makes the model look wrong for the wrong reason.
• Using only one sample per porosity level, which leaves you unable to separate geometry effects from print variation.
• Measuring flow rate with shaky timing or unreadable water levels, which adds noise that hides real permeability trends.

What Makes This Competitive

A strong version of this project does more than show that flow changes with porosity. It tests whether a model predicts the trend, the scale, and the failure points of the real samples. You can raise the level by comparing multiple boundary conditions, checking print accuracy with geometry measurements, and using statistical error analysis across repeated prints. That makes the project about model validation, not just observation.

Project Variations

• Compare gyroid lattices with another porous shape, such as cubic or Schwarz-P surfaces, to see which geometry gives higher permeability at the same porosity.
• Test different print materials, such as PLA and resin, to study how surface roughness changes measured flow.
• Add particle-tracking or dye visualization to compare flow paths in the experiment with streamlines from the simulation.

Learn More

• MIT OpenCourseWare: Search for fluid mechanics and computational fluid dynamics courses that explain flow models and porous media basics.
• USGS Water Science School: Read the free guides on permeability, porosity, and groundwater flow.
• NIH PubMed: Search for review articles on gyroid scaffolds, porous media flow, and permeability modeling.
• NASA CFD resources: Find open notes and tutorials on numerical flow methods and grid-based simulation ideas.
• Transport Phenomena: Use a library copy or preview pages to review Darcy flow, permeability, and transport concepts.