Artificial neural network analysis of heat pumps using refrigerant mixtures |
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Affiliation: | 1. School of Economics and Management, Beijing Jiaotong University, 3 Changyuancun Xizhimenwai Beijing 100044, China;2. Industry engineering center, Toulouse University – Ecole des mines d''Albi-Carmaux, Campus Jarlard, Allée des sciences, Albi, France;3. Champollion University, Place Verdun, Albi, France\n |
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Abstract: | In this study, we have investigated the performance of a vapor compression heat pump with different ratios of R12/R22 refrigerant mixtures using artificial neural networks (ANN). Experimental studies were completed to obtain training and test data. Mixing ratio, evaporator inlet temperature and condenser pressure were used as input layer, while the outputs are coefficient of performance (COP) and rational efficiency (RE). The back propagation learning algorithm with three different variants and logistic sigmoid transfer function were used in the network. It is shown that the R2 values are about 0.9999 and the RMS errors are smaller than 0.006. With these results, we believe that the ANN can be used for prediction of COP and RE as an accurate method in a heat pump. |
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