Effects of wind on the dynamics of the central jet during drop impact onto a deep-water surface

Xinan Liu, An Wang, Shuang Wang, and Dejun Dai
Phys. Rev. Fluids 3, 053602 – Published 14 May 2018

Abstract

The cavity and central jet generated by the impact of a single water drop on a deep-water surface in a wind field are experimentally studied. Different experiments are performed by varying the impacting drop diameter and wind speed. The contour profile histories of the cavity (also called crater) and central jet (also called stalk) are measured in detail with a backlit cinematic shadowgraph technique. The results show that shortly after the drop hits the water surface an asymmetrical cavity appears along the wind direction, with a train of capillary waves on the cavity wall. This is followed by the formation of an inclined central jet at the location of the drop impact. It is found that the wind has little effect on the penetration depth of the cavity at the early stage of the cavity expansion, but markedly changes the capillary waves during the retraction of the cavity. The capillary waves in turn shift the position of the central jet formation leeward. The dynamics of the central jet are dominated by two mechanisms: (i) the oblique drop impact produced by the wind and (ii) the wind drag force directly acting on the jet. The maximum height of the central jet, called the stalk height, is drastically affected by the wind, and the nondimensional stalk height H/D decreases with increasing θRe1, where D is the drop diameter, θ is the impingement angle of drop impact, and Re=ρaUwD/μa is the Reynolds number with air density ρa, wind speed Uw, and air viscosity μa.

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  • Received 15 August 2017

DOI:https://doi.org/10.1103/PhysRevFluids.3.053602

©2018 American Physical Society

Physics Subject Headings (PhySH)

Fluid Dynamics

Authors & Affiliations

Xinan Liu*, An Wang, and Shuang Wang

  • Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20742, USA

Dejun Dai

  • First Institute of Oceanography, State Oceanic Administration, Qingdao, Shandong 266061, China

  • *xliu@umd.edu
  • Present address: School of Artificial Intelligence, Xidian University, Xi'an, Shaanxi 710071, China.

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Vol. 3, Iss. 5 — May 2018

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