Title: Comparative energy and exergy analysis of water-LiBr absorption chiller configurations with ejector integration, and implementation of artificial neural network on the optimal selection

Authors: Hamid-Reza Bahrami; Samane Fazli

Addresses: Department of Mechanical Engineering, Qom University of Technology, Khodakaram Blvd., Old Qom-Tehran, Road, Qom, 1519-37195, Iran ' Department of Mechanical Engineering, Qom University of Technology, Khodakaram Blvd., Old Qom-Tehran, Road, Qom, 1519-37195, Iran

Abstract: Refrigeration, a fossil fuel-intensive industry causing ozone depletion, is exploring energy-efficient alternatives like absorption chillers. Ejectors show promise in improving absorption chiller efficiency. Four ejector-assisted single-effect absorption chillers using LiBr as refrigerant were examined. The ejectors are used in different locations of the cycle in each configuration. Results reveal that Type D performs best (COP of 1.4 and lowest condenser heat rejection). The study also demonstrates the efficacy of artificial neural networks in accurately predicting cycle performance, which is useful for HVAC applications. Additionally, the genetic algorithm is employed to determine the optimal performance of the selected configuration.

Keywords: ejector; absorption chiller; exergy; second law of thermodynamics; LiBr.

DOI: 10.1504/IJEX.2024.138087

International Journal of Exergy, 2024 Vol.43 No.4, pp.289 - 305

Received: 19 May 2023
Accepted: 26 Aug 2023
Published online: 29 Apr 2024 *

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