Energy Analysis of Water-Lithium Chloride (LiClH2O) operated Absorption Refrigeration System using ANN Approach
Dheerendra Vikram Singh1, Tikendra N Verma2
1Dheerendra Vikram Singh, Department of Mechanical Engineering, NIT- Manipur, India.
2Tikendra N Verma, Department of Mechanical Engineering, NIT Manipur, India.
Manuscript received on 18 February 2019 | Revised Manuscript received on 27 February 2019 | Manuscript published on 28 February 2019 | PP: 225-232 | Volume-8 Issue-3, February 2019 | Retrieval Number: C5718028319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The objective of this work is to exploit artificial intelligence for performing energy analysis of absorption refrigeration system (ARS) with water-lithium chloride as working fluid. Energy analysis of water-lithium chloride operated vapour absorption refrigeration system is a very intricate process due to limited thermodynamic property data points and analytical functions required for estimating the thermodynamic properties of untraditional working fluid pairs. These equations usually involve the higher order complex partial differential equations and cannot be solved using simple mathematics and are time consuming too. With the help of ANN, authors have formulated new mathematical equations for estimating thermodynamic properties of each salient state of the ARS cycle. Heat load in major component of the ARS and first law based performance indexes are calculated in this analysis. The maximum difference between the predicted results and experimental data of thermodynamic properties are less than 1%. Value of the coefficient of multiple determinations is 1 for test data set and can be considered satisfactorily for using ANN in vapour absorption refrigeration system.
Keywords: Energy Analysis, ANN, ARS, Water-Lithium Chloride, COP.
Scope of the Article: Bio-Science and Bio-Technology