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---
license: cc-by-4.0
---
# BubbleML 2.0:
**BubbleML_2** is a high-fidelity dataset of boiling simulations in 2D for three fluids (FC-72, Liquid N2 and R515B). It provides paired time-series fields stored in HDF5 (.hdf5) files together with metadata (.json) and explicit train/test splits.
---
## 🚀 Quickstart
The current available dataset subsets are-
```
"single-bubble", "pb-saturated", "pb-subcooled", "fb-velscale", "fb-chf"
```
They are chosen for each individual forecasting task in our paper, viz. Single Bubble, Saturated Pool Boiling, Subcooled Pool Boiling, Flow Boiling- Varying Inlet Velocity and
Flow Boiling- Varying Heat Flux.
```python
from datasets import load_dataset
# Load the TRAIN split
ds_train = load_dataset(
"hpcforge/BubbleML_2",
name="single-bubble",
split="train",
streaming=True, # to save disk space
trust_remote_code=True, # required to run the custom dataset script
)
# Load the TEST split
ds_test = load_dataset(
"hpcforge/BubbleML_2",
name="single-bubble",
split="test",
streaming=True,
trust_remote_code=True,
)
```
Each example in ds_train / ds_test has the following fields:
* input
NumPy array of shape (time_window=5, fields=4, HEIGHT, WIDTH)
* output
NumPy array of shape (time_window=5, fields=4, HEIGHT, WIDTH)
* fluid_params
List of 9 floats representing: Inverse Reynolds Number, Non-dimensionalized Specific Heat, Non-dimensionalized Viscosity, Non-dimensionalized Density,
Non-dimensionalized Thermal Conductivity, Stefan Number, Prandtl Number, Nucleation wait time and the Heater temperature.
```
[inv_reynolds, cpgas, mugas, rhogas, thcogas, stefan, prandtl, heater.nucWaitTime, heater.wallTemp]
```
* filename
HDF5 filename (e.g. Twall_90.hdf5)
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