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Numerical and experimental analysis of fluid force for nuclear valve  ( SCI-EXPANDED收录 EI收录)  

文献类型:期刊文献

英文题名:Numerical and experimental analysis of fluid force for nuclear valve

作者:Li, Qingye[1];Zong, Chaoyong[1];Liu, Fuwen[1];Zhang, Ao[1];Xue, Tianhang[1];Yu, Xinhai[2];Song, Xueguan[1]

机构:[1]Dalian Univ Technol, Sch Mech Engn, Dalian 116023, Peoples R China;[2]East China Univ Sci & Technol, Sch Mech & Power Engn, Shanghai 200237, Peoples R China

年份:2023

卷号:241

外文期刊名:INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES

收录:;EI(收录号:20224813184832);WOS:【SCI-EXPANDED(收录号:WOS:000895508900002)】;

基金:Acknowledgments This work was supported by the National Natural Science Foundation of China (No. 52075068) . We would also like to thank the editors and the reviewers for their constructive comments and helpful suggestions. Thanks also to Beijing Super Cloud Computing Center.

语种:英文

外文关键词:CFD; Surrogate model; Experimental measurement; Fluid force; Nuclear power plant; Valve

摘要:Nuclear safety valve is a critical piece of equipment in a nuclear power plant, which is used to prevent irreversible damage caused by a sudden increase in pressure. However, there are some instances wherein valves may fail to function properly, which can have significantly impact the safety of the entire pressure/energy system. The main causes behind this phenomenon is the effect of fluid-structure coupling between the fluid force and valve disc. To better understand the fluid force, a high-fidelity computational fluid dynamics (CFD) model is established to predict the behavior of fluid forces and the location of vortices in the valve. Moreover, a visual fluid force test rig is used to verify the accuracy of the CFD model. Based on the validated CFD model, the mechanism of fluid force differences for two typical valve discs are analyzed in detail, together with the univariate effects of groove depth and valve opening on the fluid force. Based on the univariate analysis results, the coupling effect of groove depth and valve opening on fluid force is quantified using the supervised learning algorithm and Sobol sensitivity analysis. The study provides a new perspective on the characteristics of valve fluid force, and highlights the significant potential of dynamic control and energy conservation of valves.

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