Long-term G-functions for bidirectional aquifer thermal energy storage system operation

Trained KNN Models | COMSOL Benchmark Data

Requirements

Anaconda (with Python installed)

pip install -r requirements.txt

Matlab

Curve Fitting Toolbox

Symbolic Math Toolbox

COMSOL Model

The benchmark COMSOL model can be checked from the previous work.

Getting Started

Download KNN models and place them in model/.
Download benchmark data and place them in validation_data/.
type matlab in Anaconda console.
Open main.m, change case study id, and run.
Results will be saved in results/.

To Do

Build the software as a fully Python package.

Acknowledgments

This repository and code have been developed and maintained by Kecheng Chen.

References

[1] Chen, K., Sun, X., Soga, K., Nico, P. S., and Dobson, P. F. (2024). Machine-learning-assisted long-term G functions for bidirectional aquifer thermal energy storage system operation. Energy, 301, 131638.