| --- |
| license: cc-by-nc-sa-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) |
