Abstract
In the supercritical CO2 (SCO2) Brayton cycle, the pre-cooler is employed to cool SCO2 to be near the pseudo-critical point state to minimise compression work and achieve high cycle efficiency. The dramatic variation in thermophysical properties of SCO2 makes heat transfer and flow very complex in the pre-cooler, bringing a lot of difficulty to the design of the related components and system. This study attempts to address this issue. The experiment and simulation are carried out to analyse the influences of mass flux, inlet temperature, and pressure on the thermal-hydraulic characteristics of SCO2 flows in a straight-channel printed circuit heat exchanger (PCHE) employed as a pre-cooler, and the underlying heat transfer mechanism is analysed as well. The local heat transfer coefficient (h) is higher when the phenomenon that the local temperature of SCO2 (Tf) is equal to the pseudo-critical temperature (Tpc) appears in the laminar sublayer than when this phenomenon appears in the buffer layer. The new heat transfer and flow correlations are presented, and the genetic algorithm and back-prediction (GA-BP) neural network is employed to predict the local heat transfer and flow performance. The maximum relative error between the Nusselt number (Nu) predicted by the new heat transfer correlation and Nu obtained via experiment and simulation is within ±20%. The maximum relative error between the Nu predicted by the GA-BP neural network and the Nu obtained through experiment and simulation is within ±15%. The maximum relative error between the Fanning friction factor (f) predicted by the new friction factor correlation and f obtained via experiment and simulation is within ±5%. The maximum relative error between f predicted by the GA-BP neural network and f obtained through experiment and simulation is within ±4%. The present investigations analyse the thermal-hydraulic characteristics of SCO2 in the pre-cooler prototype and could provide useful guidance for the design of pre-coolers for the SCO2 Brayton cycle.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.