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THERMODYNAMIC ANALYSIS AND SIMULATION OF A NEW COMBINED POWER AND REFRIGERATION CYCLE USING ARTIFICIAL NEURAL NETWORK

机译:基于人工神经网络的新型联合制冷循环热力学分析与仿真

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摘要

In this study, a new combined power and refrigeration cycle is proposed, which combines the Rankine and absorption refrigeration cycles. Using a binary ammonia-water mixture as the working fluid, this combined cycle produces both power and refrigeration output simultaneously by employing only one external heat source. In order to achieve the highest possible exergy efficiency, a secondary turbine is inserted to expand the hot weak solution leaving the boiler. Moreover, an artificial neural network is used to simulate the thermodynamic properties and the relationship between the input thermodynamic variables on the cycle performance. It is shown that turbine inlet pressure, as well as heat source and refrigeration temperatures have significant effects on the net power output, refrigeration output, and exergy efficiency of the combined cycle. In addition, the results of artificial neural network are in excellent agreement with the mathematical simulation and cover a wider range for evaluation of cycle performance.
机译:在这项研究中,提出了一种新的结合了朗肯和吸收式制冷循环的动力和制冷循环。使用二元氨水混合物作为工作流体,该联合循环仅使用一个外部热源即可同时产生动力和制冷输出。为了获得最大可能的火用效率,插入了一个二级涡轮机以膨胀离开锅炉的热弱溶液。此外,使用人工神经网络来模拟热力学性质以及输入热力学变量之间对循环性能的关系。结果表明,涡轮机入口压力以及热源和制冷温度对联合循环的净功率输出,制冷输出和火用效率有显着影响。此外,人工神经网络的结果与数学模拟非常吻合,涵盖了评估循环性能的更广泛范围。

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