Stochastic particle transport by deep-water irregular breaking waves

被引:2
|
作者
Eeltink, D. [1 ,2 ,3 ]
Calvert, R. [4 ,5 ]
Swagemakers, J. E. [4 ]
Xiao, Qian [2 ]
van den Bremer, T. S. [2 ,4 ]
机构
[1] MIT, Dept Mech Engn, Cambridge, MA 02139 USA
[2] Univ Oxford, Dept Engn Sci, Parks Rd, Oxford OX1 3PJ, England
[3] Ecole Polytech Fed Lausanne, Lab Theoret Phys Nanosyst, CH-1015 Lausanne, Switzerland
[4] Delft Univ Technol, Fac Civil Engn & Geosci, NL-2628 CD Delft, Netherlands
[5] Univ Edinburgh, Sch Engn, Edinburgh EH9 3FB, Scotland
基金
瑞士国家科学基金会;
关键词
waves/free-surface flows; STOKES DRIFT; LAGRANGIAN TRANSPORT; DIFFUSION; SIMULATION; DEBRIS;
D O I
10.1017/jfm.2023.671
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Correct prediction of particle transport by surface waves is crucial in many practical applications such as search and rescue or salvage operations and pollution tracking and clean-up efforts. Recent results by Deike et al. (J. Fluid Mech., vol. 829, 2017, pp. 364-391) and Pizzo et al. (J. Phys. Oceanogr., vol. 49, no. 4, 2019, pp. 983-992) have indicated transport by deep-water breaking waves is enhanced compared with non-breaking waves. To model particle transport in irregular waves, some of which break, we develop a stochastic differential equation describing both mean particle transport and its uncertainty. The equation combines a Brownian motion, which captures non-breaking drift-diffusion effects, and a compound Poisson process, which captures jumps in particle positions due to breaking. From the corresponding Fokker-Planck equation for the evolution of the probability density function for particle position, we obtain closed-form expressions for its first three moments. We corroborate these predictions with new experiments, in which we track large numbers of particles in irregular breaking waves. For breaking and non-breaking wave fields, our experiments confirm that the variance of the particle position grows linearly with time, in accordance with Taylor's single-particle dispersion theory. For wave fields that include breaking, the compound Poisson process increases the linear growth rate of the mean and variance and introduces a finite skewness of the particle position distribution.
引用
收藏
页数:26
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