Performance evaluation and sensitivity analysis of a low- capacity single-effect LiBr-H2O absorption cooling system using energy and exergy modeling

Syed Maaz  Hasan; MuhammadSaadUlHaq; Abdul Waheed  Badar; M Zahid Iqbal  Qureshi; Majid  Ali; M. Salman  Siddiqi

doi:10.6180/jase.202509_28(9).0007

Performance evaluation and sensitivity analysis of a low- capacity single-effect LiBr-H2O absorption cooling system using energy and exergy modeling

Syed Maaz Hasan¹, MuhammadSaadUlHaq², Abdul Waheed Badar³This email address is being protected from spambots. You need JavaScript enabled to view it., M Zahid Iqbal Qureshi⁴, Majid Ali², and M. Salman Siddiqi⁵

¹Department of Mechanical Engineering, School of Mechanical and Manufacturing Engineering, National University of Sciences and Technology (NUST), H-12, Islamabad, Pakistan

²U.S. Pakistan Center for Advanced Studies in Energy, National University of Sciences and Technology, H-12 Islamabad

³Mechanical Engineering Department, College of Engineering, University of Bahrain, Kingdom of Bahrain

⁴Department of Mechanical Engineering, University of Wah, Quaid Avenue, Wah Cantt, Pakistan

⁵Department of Mechanical Engineering and Technology Management, Norwegian University of Life Sciences, Norway

Received: August 23, 2023
Accepted: November 5, 2024
Publication Date: December 9, 2024

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202509_28(9).0007

In industrialized cooling systems, LiBr − H₂O is widely utilized as the predominant working fluid, particularly in absorption systems for maintaining the thermal comfort of building occupants. There is a pressing need for more energy-efficient alternatives due to the significant stride in energy consumption by HVAC systems. In this research performance characteristics of 2.5 kW air-cooled Lithium Bromide Water absorption cooling system were examined by modeling the system based on the first and second law of thermodynamics. Sensitivity analyses of the key performance indicators were performed using decision tree, a prevalent machine learning algorithm, by computing importance by keeping one factor constant while varying the other e.g. generator temperature was kept constant while the concentration of the LiBr solution was varied. Exergetic efficiency was increased by 7.95% as the generator temperature increased from 90 to 135^◦C. It was also observed that a significant portion of exergy losses occur in the generator and the absorption process. Improvement and reallocation strategies have been discussed in the conclusion.

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