Numerical and experimental analysis of cavitation characteristics in safety valves of the nuclear power second circuit using a modified cavitation model

Abstract

Cavitation frequently arises in the safety valve of nuclear power plants’ secondary circuits operating under high pressure conditions. This study integrates valve flow characteristics and velocity strain rate corrections into the Zwart-Gerber-Belamri model to accurately simulate cavitation inside the valve, reducing the impact of physical empirical coefficient variations on cavitation length prediction. Subsequently, a visualisation test rig is developed to validate the accuracy of the numerical model, and experimental cavitation results are obtained using the grayscale detection method. The evaporation/condensation coefficients are optimised using the AES-MSI model and GA based on the experimental results. The accuracy of the constructed model is validated by comparing it with experimental results obtained under various operating conditions. Finally, the high-fidelity numerical model is employed to investigate the effects of pressure drop and valve openings on cavitation, elucidating the underlying mechanisms governing cavitation variations resulting from pressure drops. Furthermore, a comprehensive equation is derived to determine the effective flow area, aiding in the identification of cavitation locations and offering insights into the relationship between cavitation behaviour and valve openings. The modified cavitation model proposed in this study can be readily extended to investigate cavitation prediction in other valves or throttle elements.

KEYWORDS:

• Safety valve
• cavitation model
• nuclear power plant
• CFD
• visualisation experiments

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.

Author statement

The research was conceptualised and guided by Xueguan Song and Qingye Li. Shuai Zhang was responsible for constructing the surrogate model, MuChen Wang conducted the visualisation experiments and handled the image processing. Chaoyong Zong and Xuyang Li undertook the CFD modelling, calculations, and data analysis.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (No. 52075068).