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license: cc-by-4.0 |
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--- |
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# BubbleML 2.0: |
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**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. |
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--- |
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## 🚀 Quickstart |
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The current available dataset subsets are- |
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``` |
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"single-bubble", "pb-saturated", "pb-subcooled", "fb-velscale", "fb-chf" |
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``` |
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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 |
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Flow Boiling- Varying Heat Flux. |
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```python |
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from datasets import load_dataset |
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# Load the TRAIN split |
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ds_train = load_dataset( |
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"hpcforge/BubbleML_2", |
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name="single-bubble", |
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split="train", |
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streaming=True, # to save disk space |
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trust_remote_code=True, # required to run the custom dataset script |
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) |
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# Load the TEST split |
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ds_test = load_dataset( |
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"hpcforge/BubbleML_2", |
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name="single-bubble", |
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split="test", |
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streaming=True, |
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trust_remote_code=True, |
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) |
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``` |
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Each example in ds_train / ds_test has the following fields: |
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* input |
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NumPy array of shape (time_window=5, fields=4, HEIGHT, WIDTH) |
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* output |
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NumPy array of shape (time_window=5, fields=4, HEIGHT, WIDTH) |
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* fluid_params |
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List of 9 floats representing: Inverse Reynolds Number, Non-dimensionalized Specific Heat, Non-dimensionalized Viscosity, Non-dimensionalized Density, |
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Non-dimensionalized Thermal Conductivity, Stefan Number, Prandtl Number, Nucleation wait time and the Heater temperature. |
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``` |
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[inv_reynolds, cpgas, mugas, rhogas, thcogas, stefan, prandtl, heater.nucWaitTime, heater.wallTemp] |
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``` |
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* filename |
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HDF5 filename (e.g. Twall_90.hdf5) |
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