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- W2912371109 abstract "Abstract The radial-inflow turbine is a key component of the organic Rankine cycle (ORC) system, and its efficiency is related to working fluid properties and working conditions. In this paper, multi-objective algorithm was employed to conduct a comparative analysis of an ORC system with different turbine efficiency models (constant and variable). The system thermal efficiency and multi-objective optimization results between the constant turbine efficiency ORC system (CTORC) and the variable turbine efficiency ORC system (VTORC) were compared, and the reasons for the difference between the CTORC and VTORC system were analyzed. Sensitivity analysis was performed to compare the difference between the CTORC system and the VTORC system at different waste flue gas inlet temperature. The results show that the system thermal efficiency of both the CTORC and the VTORC increases with the increasing evaporation temperature and decreases with the increasing condensation temperature, while the variation rate of system thermal efficiency is different between CTORC system and VTORC system. The predicted turbine efficiency is significantly different for different working fluids and different working conditions. Considering the system comprehensive performance, R236ea is the optimal working fluid for the CTORC system, while R365mfc is for the VTORC system. For different working fluids, the error caused by using constant turbine efficiency model is different. With the increasing waste flue gas inlet temperature, the error caused by using constant turbine efficiency increases for R236ea, while the error caused by using constant turbine efficiency increases first and then decreases for R365mfc." @default.
- W2912371109 created "2019-02-21" @default.
- W2912371109 creator A5029021466 @default.
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- W2912371109 date "2019-04-01" @default.
- W2912371109 modified "2023-10-12" @default.
- W2912371109 title "Comparative analysis of an organic Rankine cycle with different turbine efficiency models based on multi-objective optimization" @default.
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- W2912371109 doi "https://doi.org/10.1016/j.enconman.2019.01.117" @default.
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