add dataset

README.md

@@ -1,3 +1,63 @@
----
-license: mit
----
+---
+language:
+    - en
+arxiv:
+    - 2506.08604
+license:
+    - mit
+---
+
+# Flow Matching Meets PDEs: A Unified Framework for Physics-Constrained Generation
+
+The datasets contain the data for the **dynamic stall** and **Kolmogorov flow** cases. You can find the **reference paper [here](https://arxiv.org/abs/2506.08604)**.
+
+
+
+## Dynamic Stall dataset
+The design space is defined as a four-dimensional hypercube. The design variables are:
+| Design variable         | Symbol                                 | Description                                          | Range       |
+|-------------------------|----------------------------------------|------------------------------------------------------|-------------|
+| Free-stream Mach number | $ M_{\infty} $                         | Ratio of free-stream velocity to speed of sound      | 0.3 – 0.5   |
+| Mean angle of attack    | $ \alpha_0 $                           | Average angle between chord line and flow direction  | 5° – 10°    |
+| Pitching amplitude      | $ \alpha_s $                           | Maximum angular deviation during pitching motion     | 5° – 10°    |
+| Reduced frequency       | $ k = \dfrac{\omega c}{2V_{\infty}} $  | Non-dimensional frequency of oscillation             | 0.05 – 0.1  |
+
+The hypercube is sampled with **128 points for training** and **16 points for testing**. Each sampled point represents a nominal operating condition.
+
+Each nominal condition is perturbed as follows:
+
+$$
+x_{\text{perturbed}} = (1 + \mathcal{N}(0, 0.02)) \cdot x_{\text{nominal}}
+$$
+
+where $\mathcal{N}(0, 0.02)$ denotes a Gaussian noise term with zero mean and standard deviation 0.02.
+
+This results in **32 perturbed variations per nominal condition**, yielding a total of:
+
+- $128 \times 32 = 4096$ simulations for training
+- $16 \times 32 = 512$ simulations for testing
+
+Each simulation that corresponds to a dataset sample has 6 fields of size $128 \times 128$. The fields correspond to:
+- Absolute pressure
+- x-wall tangential velocity gradient
+- y-wall tangential velocity gradient
+- Temperature
+- Density
+- Wall shear stress
+
+Each `hdf5` file contains three arrays:
+- `fields` with shape `(conditions, samples per condition, fields, x, y)`
+- `nominal_condition` with shape `(nominal conditions, samples per condition, design variables)`
+- `real_condition` with shape `(real ominal conditions, samples per condition, design variables)`
+
+## Kolmogorov flow dataset
+The Kolmogorov flow problem spans Reynolds numbers
+in the range $[100, 500]$, using a spatial resolution of $128 \times 128$. The simulations are performed using [TorchFSM](https://zenodo.org/records/15350210). The **training dataset includes 32 different flow conditions**, while the **validation dataset contains 16 conditions**. Each condition has $1\, 024$ snapshots.
+
+Each simulation that corresponds to a dataset sample has 2 fields of size $128 \times 128$. The fields correspond to:
+- x-velocity
+- y-velocity
+
+Each `hdf5` file contains two arrays:
+- `fields` with shape `(conditions, samples per condition, fields, x, y)`
+- `reynolds` with shape `(reynolds numbers, )`

data/dynamic_stall/dynamic_stall_test.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8f0799aa5b4c19e5c641dee76d8b04f291267cd225c22a9277fc866935976779
+size 201345024

data/dynamic_stall/dynamic_stall_train.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b780e3c1d588e91d72e2307afa38b5ea6ce420bdcc5ddaacca3d03f6f4fb2734
+size 1610745856

data/kolmogorov_flow/kolmogorov_test.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c3755e086f764ad974d171d5bf3c8e1e9730d385ed0a3328efc82c3bf80d3487
+size 2147485760

data/kolmogorov_flow/kolmogorov_train.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ae954fbbb191f641e030ace2c765b7f58fd4c4360eaceb99b2895b5007498221
+size 4294969472