Aided Active Learning for Enhanced Critical Heat Flux Prediction

NURETH-21: Aided Active Learning for Enhanced Critical Heat Flux Prediction

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📄 Paper

Nabila, U.M., Radaideh, M.I., Burnett, L.A., Lin, L., Radaideh, M.I. (2025). “Aided Active Learning for Enhanced Critical Heat Flux Prediction”, In: 21st International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH-21), Busan, Korea, August 31 – September 5, 2025.

⚙️Environment Installation

To set up the environment for this project, follow these steps:

# 1. Create a new conda environment with Python 3.11
conda create -n torchgpu python=3.11
# 2. Activate the environment
conda activate torchgpu
# 3. Install required libraries
pip install -r requirements.txt

Check whether Nvidia-cuda was installed using

import torch
print(torch.cuda.is_available())

If this prints False, you can download torch+cuda from Pytorch website.

📊 How to Generate the Results

• The folder data contains input data files used by the model scripts to generate results.

• Go to the folder models and run the desired script (e.g., viAL.py) to start the training or evaluation process.

python viAL.py

Results will be saved automatically in the results folder.