Abstract
The convective heat transfer behavior of supercritical nitrogen (S-N2) has played a significant role in optimizing the design of recently emerging cryogenic cold storage and recovery systems. However, studies on S-N2 heat transfer have been relatively scarce, not to mention that there is a legitimate urge for a robust numerical model to accurately predict and explain S-N2 heat transfer under various working conditions. In this paper, both experimental and numerical studies were conducted for convective heat transfer of S-N2 in a small vertical tube. The results demonstrated that the standard k-ε model performed better for predicting the key heat transfer characteristics of S-N2 than the SST k-ω model. The effects of heat flux and inlet pressure on the heat transfer characteristics under a large mass flux were evaluated. The variation mechanisms of local heat transfer performance were revealed by illustrating radial profiles of thermophysical properties and turbulent parameters of N2. It was found that the local performance variation along the flow direction was mainly determined by the radial profile of specific heat while the variation of the best local performance with the ratio of heat flux to mass flux was mainly determined by the radial profile of turbulent viscosity.
Original language | English |
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Article number | 7773 |
Number of pages | 20 |
Journal | Energies |
Volume | 14 |
Issue number | 22 |
DOIs | |
Publication status | Published - 19 Nov 2021 |
Bibliographical note
Funding Information:Funding: This research was funded by the Engineering and Physical Sciences Research Council (EPSRC) of the United Kingdom, grant number EP/N021142/1.
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Keywords
- CFD simulation
- Convective heat transfer
- Effective thermal conductivity
- Energy storage
- Supercritical nitrogen
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Fuel Technology
- Energy Engineering and Power Technology
- Energy (miscellaneous)
- Control and Optimization
- Electrical and Electronic Engineering