Optimal design of a supercritical carbon dioxide recompression cycle using deep neural network and data mining techniques
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DOI: 10.1016/j.energy.2023.127038
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Cited by:
- He, Tianyu & Cao, Yue & Si, Fengqi & Chua, Kian Jon, 2024. "Off-design characteristics and operation strategy analysis of a compressed carbon dioxide energy storage system coupled with a combined heating and power plant," Energy, Elsevier, vol. 303(C).
- Du, Yadong & Yu, Zhiyi & Yang, Ce & Wang, Haimei & Ernest Chua, Kian Jon, 2024. "A recompression supercritical CO2 cycle using heat source storage to achieve low-frequency reactor regulation: Analysis and optimization of load capacity under safe compressor operation," Energy, Elsevier, vol. 301(C).
- Yuhui Xiao & Yuan Zhou & Yuan Yuan & Yanping Huang & Gengyuan Tian, 2023. "Research Advances in the Application of the Supercritical CO 2 Brayton Cycle to Reactor Systems: A Review," Energies, MDPI, vol. 16(21), pages 1-23, October.
- Du, Yadong & Yu, Zhiyi & Sun, Weihua & Yang, Ce & Wang, Haimei & Zhang, Hanzhi, 2024. "Chemical looping combustion-driven cooling and power cogeneration system with LNG cold energy utilization: Exergoeconomic analysis and three-objective optimization," Energy, Elsevier, vol. 295(C).
- Yu, Mingzhe & Yang, Fubin & Zhang, Hongguang & Yan, Yinlian & Ping, Xu & Pan, Yachao & Xing, Chengda & Yang, Anren, 2024. "Thermoeconomic performance of supercritical carbon dioxide Brayton cycle systems for CNG engine waste heat recovery," Energy, Elsevier, vol. 289(C).
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Keywords
Supercritical CO2 recompression cycle; Marine applications; Deep neural network; Data mining techniques; Multi-objective optimisation;All these keywords.
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