Numerical investigation on transient internal cavitating flow and spray characteristics in a single-hole diesel injector nozzle: A 3D method for cavitation-induced primary break-up

摘要

The spray development and atomization are strongly influenced by the internal nozzle flow. In this study, a 3D cavitation-induced primary break-up method is proposed based on cavitation characteristics studies. The reason why to develop this advanced standard method and abandon the total Eulerian approach has been discussed. The transient cavitation characteristics inside a single-hole diesel injector nozzle were numerically investigated. Combined with previous experimental studies, a dynamic mesh method and its related numerical model were utilized to investigate the inner cavitating flow characteristics for cases of different maximum needle lift values, injection pressures and ambient pressures. It is found that the mass flow rate increases significantly with the increase of maximum lift position for low needle lift cases. The cavitating flow for low needle lift cases requires necessary simulations and the traditional standard method with only empirical equations is not enough. It is also found that for high needle lift cases, the internal flow keeps stable for over 90 percent of the total injection process. The 3D method aims to incorporate as much flow information as possible to avoid using the total Eulerian approach. The 3D method allows for nozzle cross section with both two-dimensional and three-dimensional data. The spray experiment in a constant chamber with different injection pressure and the same ambient pressure is employed to validate the 3D method. The 3D method with transient internal flow profiles is implemented into the AVL Fire CFD codes. The 3D method, together with the typical standard method (with or without 1D method) are applied to the experimental data, including spray tip penetration (STP), spray shape and droplet diameter. The results show that the 3D method has good predictive ability on the spray development and shape, and it has better performance on droplet diameter prediction.