We present a numerical study of inception in the shear layer of a backward-facing step under the same conditions as experiments (Agarwal et al., 2018). The velocity field is shown to be in good agreement with experiments. Since inception is a stochastic process that generates small amounts of vapor for short periods of time, the effects of these small regions of vapor on the liquid density and dynamics can be neglected. Vapor is therefore treated as a passive scalar in an incompressible liquid and modeled using the same vapor transport equation as that in a fully compressible homogeneous mixture model. The model is validated against the compressible homogeneous mixture approach at incipient conditions. Both velocity and scalar fields are advanced using the implicit Crank–Nicolson scheme. However, the scalar field is solved in an inner loop at a smaller time step than the velocity field. Statistics are computed for both pressure and vapor volume fraction, and the likelihood of inception is determined. The locations of the preferred sites for cavitation are compared to experimental results and good agreement is achieved. The effects of finite rate evaporation and condensation are revealed by the probability density functions of pressure and volume fraction. The flow topology is investigated and inception is found to occur in the core of the stretched tubular vortical structures with a rotation rate four times higher than the stretching rate. These cavitating tubular structures are elongated two to three times more in their most extensive principal direction than in their intermediate principal direction, and are most likely aligned with the streamwise direction. Decreasing the cavitation number from 0.55 to 0.45 is found to drop the minimum pressure inside the vortices from −1500 Pa to −5500 Pa and increase the cavitation event rates by around O(1).
|Original language||English (US)|
|Journal||International Journal of Multiphase Flow|
|State||Published - Jan 2022|
Bibliographical noteFunding Information:
This work is supported by the United States Office of Naval Research under grant ONR N00014–17–1–2676 with Dr. Ki–Han Kim as the program manager. Computing resources were provided by the High-Performance Computing Modernization Program (HPCMP). We thank Ms. Karuna Agarwal and Professor Joseph Katz for providing the experimental data.
This work is supported by the United States Office of Naval Research under grant ONR N00014?17?1?2676 with Dr. Ki?Han Kim as the program manager. Computing resources were provided by the High-Performance Computing Modernization Program (HPCMP). We thank Ms. Karuna Agarwal and Professor Joseph Katz for providing the experimental data.
© 2021 Elsevier Ltd
- Large eddy simulation
- Shear layer