--- 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`.