Understanding Air-Film Breakup under Liquid Impacts Using Direct Numerical Simulations
Abstract
The objective of the proposed research is to develop an understanding of how the smallest microbubbles are formed in air-sea interactions. Our preliminary analysis indicates that inertial water impact phenomena (e.g., due to interactions of ship hull with water surface) often entrap air films that then form order micron thin lubrication layers in between impacting water zones. The subsequent breakup of these films can generate many microbubbles that can reside below the surface for a long time due to their small size. In naval applications these bubbles make a major contribution in ship wake bubble content, and can affect performance. In oceanography applications, microbubbles (e.g., due to natural breaking waves) play an important role in air/sea mass transfer, and affect the ecosystems in these environments. Therefore, it is of paramount importance to develop a quantitative understanding of the phenomenon responsible for the generation of these bubbles. Such understanding provides guidelines for improved hydrodynamic designs in naval applications, it also improves mass transfer models in oceanography applications. Current macroscopic air entrainment models are not quantitatively informed about the air-film breakup process. Recent progress in computing technology and the advancement of new massively parallel supercomputers provides fresh opportunities for direct probing of the detailed processes involved in the breakup of such air-films in three dimensions. We plan to utilize these capabilities, and by leveraging our previous experience in numerical analysis of two-phase flow systems, we propose to develop a detailed investigation of thin air-film breakup process to gain insight into key parameters controlling the resulting microbubbles. A statistical analysis of these simulations will be used to develop a reduced order model that can quantitatively and efficiently be integrated with macroscopic air-entrainment models for accurate prediction of their microbubble content. The proposed reduced model would alleviate the current computational resolution requirements for prediction of microbubbles by about three orders of magnitude.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 12, 2016
- Source ID
- N000141512523
Entities
People
- Ali Mani
Organizations
- Office of Naval Research
- Stanford University
- United States Navy