Datasets:
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---
license: cc-by-sa-4.0
size_categories:
- n<1K
task_categories:
- graph-ml
pretty_name: 2D external aero CFD RANS datasets, under geometrical variations
tags:
- physics learning
- geometry learning
configs:
- config_name: default
data_files:
- split: all_samples
path: data/all_samples-*
dataset_info:
description:
legal:
owner: Safran
license: CC-by-SA 4.0
data_production:
type: simulation
physics: 2D stationary RANS
simulator: elsA
split:
train:
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test:
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task: regression
in_scalars_names: []
out_scalars_names: []
in_timeseries_names: []
out_timeseries_names: []
in_fields_names: []
out_fields_names:
- Mach
- Pressure
- Velocity-x
- Velocity-y
in_meshes_names:
- /Base_2_2/Zone
out_meshes_names: []
features:
- name: sample
dtype: binary
splits:
- name: all_samples
num_bytes: 1290091704
num_examples: 400
download_size: 813895818
dataset_size: 1290091704
---
# Dataset Card
This dataset contains a single huggingface split, named 'all_samples'.
The samples contains a single huggingface feature, named called "sample".
Samples are instances of [plaid.containers.sample.Sample](https://plaid-lib.readthedocs.io/en/latest/autoapi/plaid/containers/sample/index.html#plaid.containers.sample.Sample).
Mesh objects included in samples follow the [CGNS](https://cgns.github.io/) standard, and can be converted in
[Muscat.Containers.Mesh.Mesh](https://muscat.readthedocs.io/en/latest/_source/Muscat.Containers.Mesh.html#Muscat.Containers.Mesh.Mesh).
Example of commands:
```python
from datasets import load_dataset
from plaid.containers.sample import Sample
import pickle
# Load the dataset
hf_dataset = load_dataset("PLAID-datasets/2D_profile", split="all_samples")
# Get split ids
ids_train = hf_dataset.description["split"]['train']
ids_test = hf_dataset.description["split"]['test']
# Get inputs/outputs names
in_scalars_names = hf_dataset.description["in_scalars_names"]
out_fields_names = hf_dataset.description["out_fields_names"]
# Get samples
sample = Sample.model_validate(pickle.loads(hf_dataset[ids_train[0]]["sample"]))
sample_2 = Sample.model_validate(pickle.loads(hf_dataset[ids_test[0]]["sample"]))
# Examples data retrievals
nodes = sample.get_nodes()
elements = sample.get_elements()
nodal_tags = sample.get_nodal_tags()
for fn in ['Mach', 'Pressure', 'Velocity-x', 'Velocity-y']:
field = sample.get_field(fn)
# Get the mesh and convert it to Muscat
from Muscat.Bridges import CGNSBridge
CGNS_tree = sample.get_mesh()
mesh = CGNSBridge.CGNSToMesh(CGNS_tree)
print(mesh)
```
## Dataset Details
### Dataset Description
This dataset contains 2D external aero CFD RANS solutions, under geometrical variations.
The variablity in the samples is the geometry (mesh). Outputs of interest are 4 fields. Each sample have been computed on large refined meshes, which have been cut close to the profil.
Dataset created using the [PLAID](https://plaid-lib.readthedocs.io/) library and datamodel, version 0.1.
- **Language:** [PLAID](https://plaid-lib.readthedocs.io/)
- **License:** cc-by-sa-4.0
- **Owner:** Safran
### Dataset Sources
- **Repository:** [Zenodo](https://zenodo.org/records/15155119)
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