Atomization of the optimally disturbed liquid jet
ORAL
Abstract
Atomization is understood to be initiated by modal instability. In recent work by Hwang et al. (2021), strong amplification of the interface perturbation by a multi-phase Orr-mechanism is shown as a possible pathway to distort the liquid jet in the absence of exponential instability. Our study investigates the atomization of the liquid jet initiated by the optimal initial condition, which maximizes the perturbation energy transfer from the mean flow to the surface tension energy. Numerical simulations of the optimized jets are conducted with a weakly compressible solver, charLES.
We demonstrate the multi-phase Orr-mechanism as a realizable process for atomization with various flow conditions. The comparison study between the randomly disturbed jet and the optimized jet reveals the formation of small-scale structures, and ligaments, occurring within a relatively short downstream distance in the latter case. It is shown that the emergence of small-scale structures does not necessarily coincide with the maximum interface distortion. Atomization characteristic is reported for several representative dimensionless parameters.
We demonstrate the multi-phase Orr-mechanism as a realizable process for atomization with various flow conditions. The comparison study between the randomly disturbed jet and the optimized jet reveals the formation of small-scale structures, and ligaments, occurring within a relatively short downstream distance in the latter case. It is shown that the emergence of small-scale structures does not necessarily coincide with the maximum interface distortion. Atomization characteristic is reported for several representative dimensionless parameters.
–
Publication: Hwang, H., Moin, P., & Hack, M. (2021). A mechanism for the amplification of interface distortions on liquid jets. Journal of Fluid Mechanics, 911, A51. doi:10.1017/jfm.2020.1067
Presenters
-
Hanul Hwang
Center for Turbulence Research, Stanford University
Authors
-
Hanul Hwang
Center for Turbulence Research, Stanford University
-
Dokyun Kim
Cascade Technologies, Inc.
-
Parviz Moin
Center for Turbulence Research, Stanford University, Stanford University, Center for Turbulence Research, Stanford Univ