Structure optimization of submerged water jet cavitating nozzle with a hybrid algorithm

Abstract

It is critical to obtain a suitable geometry for a cavitating nozzle of submerged water jet, since a suitable geometry determines its cavitation intensity and cavitation distribution. This paper puts forward a water jet cavitating nozzle optimization platform aiming to improve its axial maximum vapor volume fraction. Considering the influence of all eight geometric parameters of the nozzle itself, a hybrid optimization algorithm is developed to optimize the nozzle by combining with the CFD technique. After the optimization, the optimal geometry results to a 9.41% increment in the axial maximum vapor volume fraction at 50 m underwater depth, and improves the cavitation effect obviously especially in deeper water. From the results, it is found that the cylindrical section diameter, contraction angle and diffusion angle have a great influence on the axial maximum vapor volume fraction, while the inlet diameter have the least effect on the same. The optimization presented in this study can lay the foundation for further study on water jet cavitating nozzle.