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

Vijayalakshmi, Shivaprasad (Durham University, UK); Giampieri, Alessandro  (Durham University, UK); Smallbone, Andrew  (Durham University, UK); Roskilly, Anthony (Durham University, UK); Roy, Sumit  (Coventry University, UK)

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Experimental and numerical investigation to optimise liquid desiccant system for advanced air conditioning [dataset] Open Access

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.

Descriptions

Resource type: Dataset
Contributors: Creator: Vijayalakshmi, Shivaprasad ¹
Data collector: Vijayalakshmi, Shivaprasad ¹
Data collector: Roy, Sumit ²
Data curator: Giampieri, Alessandro ¹
Editor: Smallbone, Andrew ¹
Editor: Roskilly, Anthony ¹

¹ Durham University, UK
² Coventry University, UK
Funder: Engineering and Physical Sciences Research Council
European Commission
Research methods: The purpose of this study is to experimentally evaluate the effectiveness of a liquid desiccant system using CaCl2 as the desiccant by varying operating temperatures and air flow rates. Additionally, an ANN metamodel-based control strategy is proposed for implementing a hybrid thermo-chemical network with the help of real-time data. The ANN metamodel-based control strategy proposed in this study aims to utilise the ANN model's predictions to optimise system performance and reduce energy consumption.
Other description
Keyword: Liquid desiccant dehumidification
Thermochemical network
Artificial neural network
Air conditioning
Subject: Renewable energy sources
Cogeneration of electric power and heat
Neural networks (Computer science)
Air conditioning
Location: Durham, England, United Kingdom
Language: English
Cited in: doi:10.1038/s41598-025-88738-2
Identifier: doi:10.15128/r1st74cq558
Rights: Creative Commons Attribution 4.0 International (CC BY)
Publisher: Durham University
Date Created

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