## 5 Conclusions  
Due to the limited test equipment, the author could not study the cavitation behavior inside the torque converter through experiments. The cavitation behavior inside the torque \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Charge Pressure** & **Backpressure** & **Vapor Volume** & **Mass Flowrate** & **Cavitation** \\
**(MPa)** & **(MPa)** & **(10\({}^{-6}\) m\({}^{3}\))** & **(kg s\({}^{-1}\))** & **Number** \\ \hline
0.8 & 0.2 & 4.1827145 & 308.50446 & 9.474 \\
0.8 & 0.4 & 2.46 & 293.31395 & 10.480 \\
0.8 & 0.6 & 2.4342955 & 287.00041 & 10.946 \\
0.8 & 0.8 & 1.8027153 & 277.24304 & 11.731 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Cavitation numbers under various backpressure conditions. Figure 17: Vapor volume fraction distributions for one typical cycle with different backpressures (\(SR=0\)). converter calculated by the author through CFD can provide a reference for the research of turbomachine cavitation, and more accurate cavitation prediction needs to be verified by experiments. The transient turbulent and cavitation flow in a hydrodynamic torque converter was numerically investigated with a RANS turbulence model and Zwart-Gerber-Belamri cavitation model, and the simulation results were compared with experimental data. The proposed CFD model agreed well with the experimental data in Figure 6. The study focused on the evolution of cavitation and its effect on the torque characteristics, especially the formation and development of O-type cavitation and shedding cavitation structures around the stator blades. The following conclusions were made:  
(1) Under non-cavitating flow conditions, the velocity and pressure were over-predicted, which increased the prediction error for the hydrodynamic performance. Especially under the stall operating condition, cavitation reduced the mass flow rate by nearly 50 kg/s, which reduced the capacity constant by 13.23%. With cavitation taken under consideration, the pressure below the saturated vapor threshold (110 Pa) was clipped out, which accurately reflects the interaction between the cavitation and vortex field in a hydrodynamic torque converter. (2) Three cavitation forms (attached, O-type, and shedding) and four stages (inception, development, shedding, and collapse) were predicted in the stator because of the reverse reentrant jet. The reattachment point of the reverse flow was located at approximately \(x/c=0.3\) of blade length (dimensionless). The turbine cavitation was the attached type. There was significant interaction between the cavitation behavior and torque characteristics, and cavitation generated quasi-periodic fluctuations in the torque, where the cavitation shedding frequency was approximately 199 Hz. The results clarified the evolution of cavitation and the cavitation mechanism at low \(SR\)s, and they provide a theoretical reference for the optimal design of hydrodynamic torque converters with a high power density. When \(SR\leq 0.1\), cavitation mainly occurred in the turbine and stator domains, and no measurable cavitation was predicted in the pump domain where high pressure was dominant owing to the high rotation speed. When \(0.1<SR<0.3\), cavitation only occurred in the stator domain. When \(SR\geq 0.3\), visible cavitation bubbles disappeared, and cavitation had almost no effect on the hydrodynamic performance. (3) The pressure of the working chamber increased with the backpressure, which reduced the cavitation risk. Thus, increasing the working chamber pressure appears to be an effective measure for suppressing cavitation in turbomachinery. The torque converter should be designed to increase the backpressure and decrease the pressure difference between the charge pressure and backpressure, which can significantly improve the cavitation suppression effect. The cavitation suppression measures considered in this study were limited.