---
license: cc-by-nc-4.0
language:
- en
tags:
- cfd
- sciml
pretty_name: Shock-Induced Droplet Aerobreakup (SIDA)
size_categories:
- 10B<n<100B
---

# Description:

This Dataset includes 128 trajectories of time-dependent Shock-Induced Droplet Aerobreakup (SIDA). Using a Finite
Volume solver, we solve the two-dimensional (2D) axisymmetric compressible Euler equations for this multiphase problem.

* dataset_name: Shock-induced Droplet Aero-breakup, 
* PDE: 2D axisymmetric compressible Euler equations, 
* created: 08-2025,
* time_dependent: true,
* include_initial_state: true,

# Spatiotemporal Information:

* num_trajectories: 128,
* num_time_steps: 61,
* num_channels: 6,
* channel_names: ["density", "pressure", "velocity_x", "velocity_y", "schlieren", "vorticity"],
* spatial_dimensions: 2,
* spatial_grid_size: [128, 256],
* dx=dy: 1.171875000e-05

# Boundary conditions:

* west: Dirichlet,
* east: ZeroGradient,
* south: Axisymmetric,
* north: ZeroGradient


> Two separet files, "train.h5" and "test.h5", are provided. The former includes 96 trajectories for training and validation; the latter covers the 32 remaining trajectories for inference only.

> Refer to the "metadat_SIDA.json" file for more details on the dataset.

> A sample Out-of-Distribution, "OOD.h5", is added as well, which covers a higher shock Mach number across 32 trajectories. For more details, refer to "metadata_SIDA_OOD.json".

# Download:

The dataset can be downloaded, e.g., via `huggingface-cli download`.

```bash
huggingface-cli download FluidVerse/SIDA --repo-type dataset --local-dir .
```

# Extra Data Generation:

Use the instructions inside the generation script, "generator.py", for creating larger datasets. This script runs the solver specified in the "metadata_SIDA.json" file. 

# Strict Licensing Notice: 

This dataset is released under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0) and is exclusively for non-commercial research and educational purposes. Any commercial use—including, but not limited to, training machine learning models, developing generative AI tools, creating software products, or other commercial R&D applications—is strictly prohibited.