TY - JOUR
T1 - Verification and validation plus uncertainty quantification of heat transfer simulation for liquid metal in wire-wrapped rod assembly
AU - Liu, Zhenglong
AU - Zhong, Peiling
AU - Qiu, Hanrui
AU - Wang, Mingjun
AU - Tian, Wenxi
AU - Su, Guanghui
N1 - Publisher Copyright:
© 2025 Elsevier Ltd
PY - 2025/6
Y1 - 2025/6
N2 - A complete CFD best practice process is proposed, including Phenomena Identification and Ranking Table (PIRT), Verification and Validation (V&V), and Uncertainty Quantification (UQ). The heat transfer of liquid metal within a rod assembly under both normal and blocked conditions is used as an example to demonstrate the full CFD process. Key flow and heat transfer phenomena are identified, and model sensitivity analyses are performed based on these phenomena. Turbulent Prandtl models, porous blockage models and different meshing strategies sensitivity analysis are conducted. Uncertainty quantification is performed. The discretization uncertainty is calculated using the Grid Convergence Index (GCI). The convergence orders are greater than unity for all cases except the fluid temperature in the blocked condition using meshing strategy 2. The input parameter uncertainty is estimated using finite difference. The model uncertainty is derived. Under normal condition, the model uncertainty of the wall and fluid temperatures are 2.88 K and 3.37 K, respectively. Under blocked condition, the model uncertainty of wall temperature is slightly higher than fluid temperature. The wall temperature uncertainty for strategies 1 and 2 are 8.46 K and 9.03 K, while the fluid uncertainty of strategy 1 and 2 are 3.57 K and 3.06 K, respectively.
AB - A complete CFD best practice process is proposed, including Phenomena Identification and Ranking Table (PIRT), Verification and Validation (V&V), and Uncertainty Quantification (UQ). The heat transfer of liquid metal within a rod assembly under both normal and blocked conditions is used as an example to demonstrate the full CFD process. Key flow and heat transfer phenomena are identified, and model sensitivity analyses are performed based on these phenomena. Turbulent Prandtl models, porous blockage models and different meshing strategies sensitivity analysis are conducted. Uncertainty quantification is performed. The discretization uncertainty is calculated using the Grid Convergence Index (GCI). The convergence orders are greater than unity for all cases except the fluid temperature in the blocked condition using meshing strategy 2. The input parameter uncertainty is estimated using finite difference. The model uncertainty is derived. Under normal condition, the model uncertainty of the wall and fluid temperatures are 2.88 K and 3.37 K, respectively. Under blocked condition, the model uncertainty of wall temperature is slightly higher than fluid temperature. The wall temperature uncertainty for strategies 1 and 2 are 8.46 K and 9.03 K, while the fluid uncertainty of strategy 1 and 2 are 3.57 K and 3.06 K, respectively.
KW - Best practice
KW - Computational fluid dynamics
KW - Flow blockage
KW - Uncertainty quantification
KW - Verification and validation
UR - https://www.scopus.com/pages/publications/105005602858
U2 - 10.1016/j.icheatmasstransfer.2025.109114
DO - 10.1016/j.icheatmasstransfer.2025.109114
M3 - 文章
AN - SCOPUS:105005602858
SN - 0735-1933
VL - 165
JO - International Communications in Heat and Mass Transfer
JF - International Communications in Heat and Mass Transfer
M1 - 109114
ER -