Data, models and code for: Heat-integrated lean vapor recompression for MEA-based CO2 capture
Description
This dataset accompanies the article "Heat-integrated lean vapor recompression for MEA-based CO2 capture: Experimentally validated modeling and physics-guided deep learning optimization" (Energy Conversion and Management). It contains the processed datasets (Stage A and Stage B rigorous rate-based campaigns, one-at-a-time, speciation, stripping-intensity and screening runs, the NSGA-II Pareto front, and the rigorous verification, exchanger-rating and robustness runs), the trained physics-guided residual DNN surrogate models (scikit-learn/joblib) with the script that re-trains them, the Python scripts for Aspen Plus V14 automation and loop closure, and the Aspen Plus V14 flowsheets of all configurations. README.md describes the folder structure and every data column, and models/model_parameters.json lists the parameters of every trained model.
Files
Institutions
- Yangtze UniversityHubei, Jingzhou