Datasets:

PLAID-datasets
/

2D_profile

	---
	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:
	- 0
	- 1
	- 2
	- 3
	- 4
	- 5
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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
	![image/png](https://i.ibb.co/zWLTtv06/Logo-2-D-profile-large-2-consolas-100.png)
	![image/png](https://i.ibb.co/fd5njm16/2-D-profile.png)

	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)