PLAID-datasets/VKI-LS59

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. Mesh objects included in samples follow the CGNS standard, and can be converted in Muscat.Containers.Mesh.Mesh.

Example of commands:

from datasets import load_dataset
from plaid.containers.sample import Sample
import pickle

# Load the dataset
hf_dataset = load_dataset("PLAID-datasets/VKI-LS59", 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
for fn in ["sdf", "ro", "rou", "rov", "roe", "nut", "mach"]:
    field = sample.get_field(fn, base_name="Base_2_2")
M_iso = sample.get_field("M_iso", base_name="Base_1_2")
for sn in sample.get_scalar_names():
    scalar = sample.get_scalar(sn)

print("nodes 2D (flow) =", sample.get_nodes(base_name="Base_2_2"))
print("nodes 1D (blade surface) =", sample.get_nodes(base_name="Base_1_2"))
print("elements 2D (flow) =", sample.get_elements(base_name="Base_2_2"))
print("elements 1D (blade surface) =", sample.get_elements(base_name="Base_1_2"))
print("nodal_tags 2D (flow) =", sample.get_nodal_tags(base_name="Base_2_2"))

# inputs
nodes = sample.get_nodes(base_name="Base_2_2")
elements = sample.get_elements(base_name="Base_2_2")
nodal_tags = sample.get_nodal_tags(base_name="Base_2_2")
sdf = sample.get_field("sdf", base_name="Base_2_2")
angle_in = sample.get_scalar("angle_in")
mach_out = sample.get_scalar("mach_out")

# outputs
mach = sample.get_field("mach", base_name="Base_2_2")
nut = sample.get_field("nut", base_name="Base_2_2")

for sn in ["Q", "power", "Pr", "Tr", "eth_is", "angle_out"]:
    outscalar = sample.get_scalar(sn)

# Get the mesh and convert it to Muscat
from Muscat.Bridges import CGNSBridge
CGNS_tree = sample.get_mesh()
mesh_fluid = CGNSBridge.CGNSToMesh(CGNS_tree, baseNames=["Base_2_2"])
print(mesh_fluid)
mesh_blade = CGNSBridge.CGNSToMesh(CGNS_tree, baseNames=["Base_1_2"])
print(mesh_blade)

Dataset Details

Dataset Description

This dataset contains 2D internal aero CFD RANS solutions, under geometrical variations, based on the VKI-LS59 blade.

The variablity in the samples are 2 input scalars and the geometry (mesh) - the signed distance function is also provided and can be used as an input field. Outputs of interest are 7 fields (6 2D-fields and 1 1D-field) and 6 scalars.

Eight nested training sets of sizes 8 to 671 are provided, with complete input-output data. A testing set of size 168 is provided, for which outputs are not provided.

Dataset created using the PLAID library and datamodel, version: 0.1.

• Language: PLAID
• License: cc-by-sa-4.0
• Owner: Safran

Dataset Sources

• Repository: Zenodo