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---
license: cc-by-4.0
task_categories:
- time-series-forecasting
size_categories:
- n<1K
tags:
- computational-fluid-dynamics
- graph-neural-networks
- unstructured-mesh
- openlb
- hdf5
pretty_name: OpenLB MultiGeometry Flow 456
---
# OpenLB MultiGeometry Flow 456
OpenLB MultiGeometry Flow 456 is an openly available collection of 456
independent two-dimensional unsteady-flow trajectories around eight obstacle
families on variable triangular meshes. It is created and maintained by
[`DingDong1921`](https://huggingface.co/DingDong1921).
## Scale and splits
- 408 train, 24 validation, and 24 test trajectories.
- 57 trajectories for each of eight families: ellipse, triangle, rectangle,
pentagon, smooth star, irregular, bunny, and elephant.
- 601 frames per trajectory over dimensionless time `0:0.1:60`.
- 2,831--4,365
mesh nodes per trajectory (mean 3580.2).
- 28.774 GiB of HDF5 payload.
- Reynolds numbers 500--1000 in increments of 50.
- Channels `(u, v, p)`: two velocity components and recovered
density-normalized specific pressure.
The three splits are predefined for reproducible comparisons. Test files are
publicly accessible, so this is a conventional held-out split rather than a
secret benchmark. When reporting a clean test result, choose methods and
hyperparameters using only train and validation data.
All eight geometry families occur in training. The supplied split supports
within-family geometry/parameter generalization studies; it does not establish
unseen-family generalization.
## Download
Download the complete dataset:
```bash
hf download DingDong1921/openlb-multigeometry-flow \
--repo-type dataset \
--local-dir openlb-multigeometry-flow
```
Download one split:
```bash
hf download DingDong1921/openlb-multigeometry-flow \
--repo-type dataset \
--include "data/test/*" \
--local-dir openlb-multigeometry-flow
```
Inspect one trajectory after download:
```bash
python examples/load_one_case.py data/train/ellipse_00.h5 --frame 0
```
See `metadata/schema.md`, `metadata/provenance.md`, and
`metadata/cases.jsonl` before constructing a loader. Each manifest row records
the split, geometry, physical/numerical parameters, source-code identities,
file size, and SHA-256 identity.
## Representative previews
| Family | Shared-scale frame at `t*=30` | Full trajectory |
| --- | --- | --- |
| Ellipse | ![](previews/ellipse_00_t30.png) | [GIF](previews/ellipse_00_speed_pressure.gif) |
| Triangle | ![](previews/triangle_00_t30.png) | [GIF](previews/triangle_00_speed_pressure.gif) |
| Rectangle | ![](previews/rectangle_00_t30.png) | [GIF](previews/rectangle_00_speed_pressure.gif) |
| Pentagon | ![](previews/pentagon_00_t30.png) | [GIF](previews/pentagon_00_speed_pressure.gif) |
| Smooth star | ![](previews/smooth_star_00_t30.png) | [GIF](previews/smooth_star_00_speed_pressure.gif) |
| Irregular | ![](previews/irregular_00_t30.png) | [GIF](previews/irregular_00_speed_pressure.gif) |
| Bunny | ![](previews/bunny_00_t30.png) | [GIF](previews/bunny_00_speed_pressure.gif) |
| Elephant | ![](previews/elephant_00_t30.png) | [GIF](previews/elephant_00_speed_pressure.gif) |
## Numerical semantics and limitations
- Solver: OpenLB 1.9.0, D2Q9/TRT, cold start, fifth-order inlet/farfield ramp,
convection outlet, and no-slip obstacle wall.
- Pressure is reconstructed from the unsteady Navier--Stokes relation and fixed
to zero at the right outlet. It is not a direct raw LBM pressure field.
- The inlet/farfield ramp ends at dimensionless time `t*=15.025`; early windows
should not be treated as stationary-boundary data.
- The data are generated by OpenLB and are not interchangeable with Nektar++
trajectories without a matched-semantics comparison.
- Representative images are navigation aids. Visual plausibility alone does
not establish physical correctness.
## License and attribution
The generated dataset payload, dataset-specific metadata, documentation, and
previews are released under
[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Cite or attribute
the dataset to `DingDong1921` and link this repository. OpenLB, DGN4CFD, and
source geometry assets retain their own licenses and are acknowledged in
`metadata/provenance.md`.