Numerical study of a generic ship’s airwake for understanding bi-stability mechanism
Journal article, 2024

A distinguishing feature of the bi-stable wake is that the wake persists in either of two preferred states for a sufficiently long time. Aiming to understand the persistence mechanism, this paper numerically investigates the airwake characteristics of the Chalmers ship model (CSM) using large eddy simulation with a wall-adapting local-eddy viscosity model and is complemented by experimental testings for validations. There are two cases of interest: (i) the baseline CSM with a sharp-edged superstructure front that induces massive boundary layer separation; (ii) the front-rounded (FR) CSM with suppressed flow separation. During a characteristic time (t∗) of 1142 (26.5 s), the baseline case has a frequently switching wake, whereas the FR wake maintains a stable asymmetric structure with only one switch attempt. To understand the different wake behaviours, the study starts by analysing wake flow structures, vortex cores and the wake dynamics, followed by investigating the instantaneous flow physics. Results suggest that the baseline wake has a weak bi-stable pattern, whereas the FR wake behaves similarly to a reflectional symmetry breaking state of a potential bi-stable wake. The wake switching is found to be driven by the tilting of (vertical-oriented) z-vorticity sheets from either side of the base toward the centre. This tilting behaviour is subjected to the high-magnitude vorticity that sheds from the upstream flow separation at the front sharp edges. With the sharp edges rounded in the FR case, the upstream vorticity is mitigated and the tilting effect is significantly reduced, leading to a more stable wake structure. The reasoning provided in the paper potentially explains the persistence mechanism of the bi-stable wake.

wakes

Author

Kewei Xu

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Xinchao Su

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Isak Jonsson

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Rickard Bensow

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Sinisa Krajnovic

Chalmers, Mechanics and Maritime Sciences (M2)

Journal of Fluid Mechanics

0022-1120 (ISSN) 1469-7645 (eISSN)

Vol. 991 A6

Machine Learning Driven Air Flow Control For Reduced Energy Consumption of Ships

Chalmers Transport Area of Advance, 2021-11-01 -- 2023-10-31.

Subject Categories

Applied Mechanics

Fluid Mechanics and Acoustics

DOI

10.1017/jfm.2024.511

More information

Latest update

12/11/2024