TY - JOUR
T1 - Heat transfer coefficient for upward forced convective flows of heated supercritical carbon dioxide in vertical tubes
AU - Lau, Kwun Ting
AU - Zhao, Jiyun
AU - Hibiki, Takashi
PY - 2025/4
Y1 - 2025/4
N2 - Accurate heat transfer prediction is crucial for optimizing supercritical power cycles. This study presents new Nusselt number correlations for forced convection heat transfer of supercritical carbon dioxide flowing upward in heated tubes. Existing correlations often suffer from reduced accuracy near the pseudocritical point. The study addresses this challenge by employing a systematic correlation modelling framework to develop region-specific correlations tailored to distinct fluid regions, namely liquid-like, near-pseudocritical, and gas-like regions. A novel interpolation methodology utilizing sigmoid functions is implemented to ensure smooth transitions between these regions. Furthermore, stability functions based on kinematic viscosity are introduced to enhance the stability of the correlations during iterative processes. The resulting three-variable correlation, incorporating the Reynolds number, Prandtl number, and a stability function, demonstrates significantly improved accuracy relative to existing correlations, achieving a maximum percentage error of 52 % and a mean absolute percentage error of 11 %. This work provides valuable tools for the design and optimization of supercritical power cycles, particularly during transient events in which precise heat transfer predictions are essential. © 2025 Elsevier Ltd
AB - Accurate heat transfer prediction is crucial for optimizing supercritical power cycles. This study presents new Nusselt number correlations for forced convection heat transfer of supercritical carbon dioxide flowing upward in heated tubes. Existing correlations often suffer from reduced accuracy near the pseudocritical point. The study addresses this challenge by employing a systematic correlation modelling framework to develop region-specific correlations tailored to distinct fluid regions, namely liquid-like, near-pseudocritical, and gas-like regions. A novel interpolation methodology utilizing sigmoid functions is implemented to ensure smooth transitions between these regions. Furthermore, stability functions based on kinematic viscosity are introduced to enhance the stability of the correlations during iterative processes. The resulting three-variable correlation, incorporating the Reynolds number, Prandtl number, and a stability function, demonstrates significantly improved accuracy relative to existing correlations, achieving a maximum percentage error of 52 % and a mean absolute percentage error of 11 %. This work provides valuable tools for the design and optimization of supercritical power cycles, particularly during transient events in which precise heat transfer predictions are essential. © 2025 Elsevier Ltd
KW - Forced convection
KW - Nusselt number correlation
KW - Supercritical carbon dioxide
KW - Systematic correlation modelling
KW - Upward flow
UR - http://www.scopus.com/inward/record.url?scp=85218641851&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85218641851&origin=recordpage
U2 - 10.1016/j.icheatmasstransfer.2025.108732
DO - 10.1016/j.icheatmasstransfer.2025.108732
M3 - RGC 21 - Publication in refereed journal
SN - 0735-1933
VL - 163
JO - International Communications in Heat and Mass Transfer
JF - International Communications in Heat and Mass Transfer
M1 - 108732
ER -