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A computational model is developed for the parametric investigation of single-effect and series flow double-effect LiBr/H2O absorption refrigeration systems. The effects of generator, absorber, condenser, evaporator and dead state temperatures are examined on the performance of these systems. The parameters computed are coefficient of performance (COP), exergy destruction rates, thermal exergy loss rates, irreversibility and exergetic efficiency. The results indicate that COP and exergetic efficiency of both the systems increase with increase in the generator temperature. There exist different optimum values of generator temperature for maximum COP and maximum exergetic efficiency. The optimum generator temperature is lower corresponding to maximum exergetic efficiency as compared to optimum generator temperature corresponding to maximum COP. The effect of increase in absorber, condenser and evaporator temperatures is to decrease the exergetic efficiency of both the systems. The irreversibility is highest in absorber in both systems. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents a computer-based first law and exergy analysis applied to vapour compression refrigeration systems for determining subcooling and superheating effects of environmentally safe new refrigerants. Three refrigerants are considered: R134a, R407c and R410a. It is found that subcooling and superheating temperatures directly influence the system performance as both condenser and evaporator temperatures are affected. The thermodynamic properties of the refrigerants are formulated using artificial neural network (ANN) methodology. Six ANNs were trained to predict various properties of the three refrigerants. The training and validation of the ANNs were performed with good accuracy. The correlation coefficient obtained when unknown data were used to the networks were found to be equal or very near to 1 which is very satisfactory. Additionally, the present methodology proved to be much better than the linear multiple regression analysis. From the analysis of the results it is found that condenser and evaporator temperatures have strong effects on coefficient of performance (COP) and system irreversibility. Also both subcooling and superheating affect the system performance. This effect is similar for R134a and R407c, and different for R410a. [ABSTRACT FROM AUTHOR]