Experiments and Heat Transfer Correlation Validations of Low-Parameter Region of sCO2 Flow in a Long Thin Vertical Loop

The focus of this study is to accurately predict the convective heat transfer of CO2 to ensure the safe and efficient design of supercritical and trans-critical CO2 energy systems. The heat transfer performance of CO2 is crucial for the stable operation of these systems. This research study explored the flow and heat transfer behavior of CO2 in a long thin vertical loop through experiments. A range of key parameters were set in the experiments to ensure the broad coverage of operating conditions. The inlet temperature was set between 10 °C and 45 °C, the pressure ranged from 6.0 to 9.0 MPa, mass fluxes varied from 500 to 1500 kg/m2s, and the heat flux reached up to 300 kW/m2. Experiments were performed at Reynolds number 104. By adjusting these parameters, the experiments were able to simulate CO2 heat transfer performance under various real-world conditions. Additionally, numerical simulations were employed to further analyze CO2’s flow and heat transfer behavior. Different turbulence models were tested, and the results showed that the SST k-ω model can best predict CO2 convective heat transfer, effectively capturing the complex heat transfer characteristics under varying flow conditions. The research outcomes were compared with established correlations through the Nusselt number, and while a ±30% uncertainty was observed, the overall agreement was satisfactory. This indicates that the experimental and simulation results are within a reasonable range, confirming their reliability.

Authors

Institutions

Publication Details

Journal
Energies
Published
2024-11-29
DOI
https://doi.org/10.3390/en17236010
Citations
3
Primary Topic
Heat transfer and supercritical fluids
Type
article
Field-Weighted Citation Impact
1.12

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Experiments and Heat Transfer Correlation Validations of Low-Parameter Region of sCO2 Flow in a Long Thin Vertical Loop

Gang Zeng, Runjie Song, Yongchang Feng, Lin Chen et al.
3 citations
Energies
Heat transfer and supercritical fluids
1.12
article

Experiments and Heat Transfer Correlation Validations of Low-Parameter Region of sCO2 Flow in a Long Thin Vertical Loop

Gang Zeng, Runjie Song, Yongchang Feng, Lin Chen, Igor Pioro, Dong Fang Yang, Deqing Mei
article en
3 citations

Abstract

The focus of this study is to accurately predict the convective heat transfer of CO2 to ensure the safe and efficient design of supercritical and trans-critical CO2 energy systems. The heat transfer performance of CO2 is crucial for the stable operation of these systems. This research study explored the flow and heat transfer behavior of CO2 in a long thin vertical loop through experiments. A range of key parameters were set in the experiments to ensure the broad coverage of operating conditions. The inlet temperature was set between 10 °C and 45 °C, the pressure ranged from 6.0 to 9.0 MPa, mass fluxes varied from 500 to 1500 kg/m2s, and the heat flux reached up to 300 kW/m2. Experiments were performed at Reynolds number 104. By adjusting these parameters, the experiments were able to simulate CO2 heat transfer performance under various real-world conditions. Additionally, numerical simulations were employed to further analyze CO2’s flow and heat transfer behavior. Different turbulence models were tested, and the results showed that the SST k-ω model can best predict CO2 convective heat transfer, effectively capturing the complex heat transfer characteristics under varying flow conditions. The research outcomes were compared with established correlations through the Nusselt number, and while a ±30% uncertainty was observed, the overall agreement was satisfactory. This indicates that the experimental and simulation results are within a reasonable range, confirming their reliability.

EnergiesVol. 17(23)
Jiangsu University (CN), Chinese Academy of Sciences (CN), Ontario Tech University (CA), Institute of Engineering Thermophysics (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, Jiangsu University, International Atomic Energy Agency
Affordable and clean energy
Openalex Percentile: Top 24%
Heat transfer and supercritical fluids
1.12
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.