| Title |
Lessons Learned from the Prediction of Cavitating Flow inside a Sharp-edged Orifice using Different RANS Turbulence Models |
| Authors |
Gong Hee Lee ; June Ho Bae |
| DOI |
https://doi.org/10.6110/KJACR.2020.32.5.249 |
| Keywords |
캐비테이션; 전산유체역학; 가동중시험; 오리피스; 난류모델 Cavitation; Computational fluid dynamics; In-service testing; Orifice; Turbulence model |
| Abstract |
In-service testing (IST) related system in the nuclear power plant has various types and sizes of orifices for flow control and decompression. Rapid flow acceleration and accompanying pressure drop may cause cavitation inside the orifice, which may result in orifice degradation and structural damage. Since cavitating flows involve complex turbulent two-phase flows, the accurate simulation of this flow by using the available computational fluid dynamics (CFD) software is still a great challenge. In this paper, to assess the prediction accuracy of different Reynolds-averaged Navier-Stokes (RANS)-based turbulence models for the analysis of cavitating flow inside a sharp-edged orifice, the simulation was conducted with the commercial CFD software, ANSYS CFX R18.1. The predicted results were then compared with the correlation based on measured data. Through this comparative study, it was concluded that turbulence models are one of the main factors providing the uncertainties in the simulation of the orifice cavitation flow and therefore, licensing applicants should carefully validate the appropriate selection of the turbulence models when they use the computational result for the orifice cavitation flow as the base data of a licensing document. |