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# 3D Wind Flow Around Building Visualization | |
This interactive application demonstrates computational fluid dynamics (CFD) simulation of wind flow around a parameterized building using deep learning. The model was trained using NVIDIA Modulus to solve the Navier-Stokes equations with turbulence modeling. | |
## Features | |
- **Real-time Visualization**: Instantly see how wind flows around buildings of different sizes and positions | |
- **Interactive Parameters**: | |
- Building position (X, Y) | |
- Building dimensions (width, depth, height) | |
- **Multiple Views**: | |
- Velocity magnitude at mid-height | |
- Pressure distribution | |
- 3D streamlines showing flow patterns | |
## Technical Details | |
- **Physics**: 3D steady-state Navier-Stokes with turbulence model | |
- **Domain**: [0,10] x [0,5] x [0,5] meters | |
- **Inlet Conditions**: 10 m/s uniform flow | |
- **Model**: FourierNet trained using NVIDIA Modulus | |
- **Hardware**: GPU-accelerated inference | |
## How to Use | |
1. Use the sliders in the sidebar to adjust building parameters | |
2. The visualizations will update in real-time: | |
- Top left: Velocity magnitude contour | |
- Top right: Pressure distribution | |
- Bottom: 3D streamlines with building geometry | |
3. You can rotate and zoom the 3D view using your mouse | |
## About | |
This demo showcases the application of deep learning to computational fluid dynamics, enabling real-time prediction of complex flow fields. The model was trained on parametric building geometries to understand flow patterns and pressure distributions around buildings of varying sizes and positions. |