Oil droplet transport under non-breaking waves: An eulerian RANS approach combined with a lagrangian particle dispersion model

Roozbeh Golshan, Michel C. Boufadel, Victor A. Rodriguez, Xiaolong Geng, Feng Gao, Thomas King, Brian Robinson, Andrés E. Tejada-Martínez

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Oil droplet transport under a non-breaking deep water wave field is investigated herein using Computational Fluid dynamics (CFD). The Reynolds-averaged Navier–Stokes (RANS) equations were solved to simulate regular waves in the absence of wind stress, and the resulting water velocities agreed with Stokes theory for waves. The RANS velocity field was then used to predict the transport of buoyant particles representing oil droplets under the effect of non-locally generated turbulence. The RANS eddy viscosity exhibited an increase with depth until reaching a maximum at approximately a wave height below the mean water level. This was followed by a gradual decrease with depth. The impact of the turbulence was modeled using the local value of eddy diffusivity in a random walk framework with the added effects of the gradient of eddy diffusivity. The vertical gradient of eddy viscosity increased the residence time of droplets in the water column region of high diffusivity; neglecting the gradient of eddy diffusivity resulted in a deviation of the oil plume centroid by more than a half a wave height after 10 wave periods.

Original languageEnglish (US)
Article number7
JournalJournal of Marine Science and Engineering
Volume6
Issue number1
DOIs
StatePublished - Jan 15 2018

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Water Science and Technology
  • Ocean Engineering

Keywords

  • Lagrangian particle dispersion
  • Non-breaking ocean waves
  • Oil spill model
  • RANS
  • Random walk method

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