Effects of turbulent heat diffusion and viscosity on the simulation of turbulent mixing in autonomous PWR subchannel analysis software

In this paper the turbulent mixing models of several domestic autonomous PWR subchannel software under review by the national nuclear safety administration were evaluated and studied. Firstly, it is found that most of these subchannel software adopt the equal-mass turbulent mixing model. Then, an experimental validation study was performed on the equal-mass turbulent mixing model. Significant variations in the model’s computational coefficients were observed under different operating conditions. Finally, parameter sensitivity analysis and engineering validation were conducted. It is obtained: In single-phase conditions, energy transfer between hot and cold channels is insignificant, while momentum transfer dominates. Effective simulation of turbulent mixing is achieved by adjusting the turbulent dynamic viscosity coefficient M t . In two-phase conditions, energy transfer between hot and cold channels dominates, while the influence of momentum transfer is negligible. Effective simulation of turbulent mixing is achieved by adjusting the turbulent thermal diffusion coefficient K t . In actual PWR nuclear power plant operations, the core condition is primarily a two-phase state with subcooled boiling. Therefore, for the current subchannel software, turbulent mixing is effectively simulated mainly by adjusting the turbulent thermal diffusion coefficient K t , while the influence of turbulent dynamic viscosity is generally neglected.

Authors

Institutions

Publication Details

Journal
International Journal of Advanced Nuclear Reactor Design and Technology
Published
2025-11-20
DOI
https://doi.org/10.1016/j.jandt.2025.11.001
Primary Topic
Heat transfer and supercritical fluids
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effects of turbulent heat diffusion and viscosity on the simulation of turbulent mixing in autonomous PWR subchannel analysis software

Xinli Gao, Qiao Xue-dong, Bin Jia, Guangyu Zhu et al.
International Journal of Advanced Nuclear Reactor Design and Technology
Heat transfer and supercritical fluids
article

Effects of turbulent heat diffusion and viscosity on the simulation of turbulent mixing in autonomous PWR subchannel analysis software

Xinli Gao, Qiao Xue-dong, Bin Jia, Guangyu Zhu, He Xiao-Qiang, An Jie-Ru
article en

Abstract

In this paper the turbulent mixing models of several domestic autonomous PWR subchannel software under review by the national nuclear safety administration were evaluated and studied. Firstly, it is found that most of these subchannel software adopt the equal-mass turbulent mixing model. Then, an experimental validation study was performed on the equal-mass turbulent mixing model. Significant variations in the model’s computational coefficients were observed under different operating conditions. Finally, parameter sensitivity analysis and engineering validation were conducted. It is obtained: In single-phase conditions, energy transfer between hot and cold channels is insignificant, while momentum transfer dominates. Effective simulation of turbulent mixing is achieved by adjusting the turbulent dynamic viscosity coefficient M t . In two-phase conditions, energy transfer between hot and cold channels dominates, while the influence of momentum transfer is negligible. Effective simulation of turbulent mixing is achieved by adjusting the turbulent thermal diffusion coefficient K t . In actual PWR nuclear power plant operations, the core condition is primarily a two-phase state with subcooled boiling. Therefore, for the current subchannel software, turbulent mixing is effectively simulated mainly by adjusting the turbulent thermal diffusion coefficient K t , while the influence of turbulent dynamic viscosity is generally neglected.

International Journal of Advanced Nuclear Reactor Design and TechnologyVol. 7(4)
Nuclear and Radiation Safety Center (CN)
Openalex Percentile: Top 63%
Heat transfer and supercritical fluids
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.