Experimental and numerical investigation to optimise liquid desiccant system for advanced air conditioning

Shivaprasad, K. V.; Roy, Sumit; Giampieri, Alessandro; Smallbone, Andrew; Roskilly, Anthony Paul

doi:10.1038/s41598-025-88738-2

Experimental and numerical investigation to optimise liquid desiccant system for advanced air conditioning

Shivaprasad, K. V.; Roy, Sumit; Giampieri, Alessandro; Smallbone, Andrew; Roskilly, Anthony Paul

Authors

Dr Shivaprasad Vijayalakshmi shivaprasad.k.vijayalakshmi@durham.ac.uk
Assistant Professor (Research)

Dr Sumit Roy sumit.roy@durham.ac.uk
Academic Visitor

Dr Alessandro Giampieri alessandro.giampieri@durham.ac.uk
Postdoctoral Research Associate

Professor Andrew Smallbone andrew.smallbone@durham.ac.uk
Professor

Professor Tony Roskilly anthony.p.roskilly@durham.ac.uk
Professor

Abstract

This study aims to experimentally demonstrate a liquid desiccant systems effectiveness by using thermo-chemical fluid, such as aqueous solution of calcium chloride. This study evaluated the effect of operating temperatures on air properties (temperature, relative humidity, and moisture content) and system effectiveness by varying air flow rates. The system’s functionality was influenced by the operational temperature and air flow rate, and the dehumidification effectiveness was higher at low operating temperatures and low airflow rates. An ANN metamodel-based control strategy is also proposed for implementation in hybrid thermo-chemical networks with the help of system performance data and real-time data. The suggested ANN model’s results were validated using a variety of measuring techniques, including the RMSE, MAPE, correlation (R), and coefficient of determination (R2). The proposed ANN analysis achieved an excellent correlation between predicted and experimentally measured data.

Citation

Shivaprasad, K. V., Roy, S., Giampieri, A., Smallbone, A., & Roskilly, A. P. (2025). Experimental and numerical investigation to optimise liquid desiccant system for advanced air conditioning. Scientific Reports, 15, Article 7151. https://doi.org/10.1038/s41598-025-88738-2

Journal Article Type	Article
Acceptance Date	Jan 30, 2025
Online Publication Date	Feb 28, 2025
Publication Date	Feb 28, 2025
Deposit Date	Mar 10, 2025
Publicly Available Date	Mar 10, 2025
Journal	Scientific Reports
Electronic ISSN	2045-2322
Publisher	Nature Research
Peer Reviewed	Peer Reviewed
Volume	15
Article Number	7151
DOI	https://doi.org/10.1038/s41598-025-88738-2
Keywords	Thermochemical network, Artificial neural network, Air conditioning., Liquid desiccant dehumidification
Public URL	https://durham-repository.worktribe.com/output/3560258