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不可逆定常流勒诺循环的功率与热效率优化

Power and Thermal Efficiency Optimization of an Irreversible Steady-Flow Lenoir Cycle.

作者信息

Wang Ruibo, Ge Yanlin, Chen Lingen, Feng Huijun, Wu Zhixiang

机构信息

Institute of Thermal Science and Power Engineering, Wuhan Institute of Technology, Wuhan 430205, China.

School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China.

出版信息

Entropy (Basel). 2021 Apr 2;23(4):425. doi: 10.3390/e23040425.

Abstract

Using finite time thermodynamic theory, an irreversible steady-flow Lenoir cycle model is established, and expressions of power output and thermal efficiency for the model are derived. Through numerical calculations, with the different fixed total heat conductances (UT) of two heat exchangers, the maximum powers (Pmax), the maximum thermal efficiencies (ηmax), and the corresponding optimal heat conductance distribution ratios (uLP(opt)) and (uLη(opt)) are obtained. The effects of the internal irreversibility are analyzed. The results show that, when the heat conductances of the hot- and cold-side heat exchangers are constants, the corresponding power output and thermal efficiency are constant values. When the heat source temperature ratio (τ) and the effectivenesses of the heat exchangers increase, the corresponding power output and thermal efficiency increase. When the heat conductance distributions are the optimal values, the characteristic relationships of P-uL and η-uL are parabolic-like ones. When UT is given, with the increase in τ, the Pmax, ηmax, uLP(opt), and uLη(opt) increase. When τ is given, with the increase in UT, Pmax and ηmax increase, while uLP(opt) and uLη(opt) decrease.

摘要

运用有限时间热力学理论,建立了不可逆定常流勒诺瓦循环模型,并推导了该模型的功率输出和热效率表达式。通过数值计算,针对两个热交换器不同的固定总热导率(UT),得到了最大功率(Pmax)、最大热效率(ηmax)以及相应的最优热导率分配比(uLP(opt))和(uLη(opt))。分析了内部不可逆性的影响。结果表明,当热侧和冷侧热交换器的热导率为常数时,相应的功率输出和热效率为恒定值。当热源温度比(τ)和热交换器的效能增加时,相应的功率输出和热效率增加。当热导率分布为最优值时,P - uL和η - uL的特征关系呈抛物线状。当给定UT时,随着τ的增加,Pmax、ηmax、uLP(opt)和uLη(opt)增加。当给定τ时,随着UT的增加,Pmax和ηmax增加,而uLP(opt)和uLη(opt)减小。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a713/8066634/b153004b2730/entropy-23-00425-g009.jpg

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