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A mechanism for the increased wave-induced drift of floating marine litter

Published online by Cambridge University Press:  18 March 2021

R. Calvert*
Affiliation:
Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UKSchool of Engineering, The University of Edinburgh, Edinburgh EH9 3FB, UK
M.L. McAllister
Affiliation:
Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
C. Whittaker
Affiliation:
Department of Civil and Environmental Engineering, University of Auckland, Auckland 1010, New Zealand
A. Raby
Affiliation:
School of Engineering, University of Plymouth, Plymouth PL4 8AA, UK
A.G.L. Borthwick
Affiliation:
School of Engineering, The University of Edinburgh, Edinburgh EH9 3FB, UK
T.S. van den Bremer
Affiliation:
Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UKFaculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 CD Delft, The Netherlands
*
†Email address for correspondence: ross.calvert@eng.ox.ac.uk

Abstract

Periodic water waves generate Stokes drift as manifest from the orbits of Lagrangian particles not fully closing. Stokes drift can contribute to the transport of floating marine litter, including plastic. Previously, marine litter objects have been considered to be perfect Lagrangian tracers, travelling with the Stokes drift of the waves. However, floating marine litter objects have large ranges of sizes and densities, which potentially result in different rates of transport by waves due to the non-Lagrangian behaviour of the objects. Through a combination of theory and experiments for idealised spherical objects in deep-water waves, we show that different objects are transported at different rates depending on their size and density, and that larger buoyant objects can have increased drift compared with Lagrangian tracers. We show that the mechanism for the increased drift observed in our experiments comprises the variable submergence and the corresponding dynamic buoyancy force components in a direction perpendicular to the local water surface. This leads to an amplification of the drift of these objects compared to the Stokes drift when averaged over the wave cycle. Using an expansion in wave steepness, we derive a closed-form approximation for this increased drift, which can be included in ocean-scale models of marine litter transport.

Information

Type
JFM Papers
Copyright
© The Author(s), 2021. Published by Cambridge University Press
Figure 0

Figure 1.Diagram of the two coordinate systems used to describe a floating object of diameter $D$: a stationary laboratory coordinate system ($x$, $z$) and a vertically translating and rotating coordinate system ($\tau$, $n$) with its origin at the vertical position of the free surface $z=\eta _p$ and the $\tau$-axis aligned tangential to the free surface. The vector $\boldsymbol {x}_p$ locates the centre of the object relative to the origin of the stationary coordinate system, $\tan \theta =\partial \eta /\partial x$ is the slope of the free surface and $s$ is the (variable) submergence.

Figure 1

Figure 2.Diagrams of (a) the submerged volume $V_{{s}}$ as a function of the variable submergence $s(t)$; (b) the projected area of a submerged sphere moving in the normal direction ($\boldsymbol {e}_n$); and (c) the projected area of a submerged sphere moving in the tangential direction ($\boldsymbol {e}_\tau$). All diagrams are shown in the ($\tau$, $n$) coordinate system.

Figure 2

Table 1.First- and second-order solutions for the kinematic properties of deep-water surface gravity waves, with $A_0= a_0\hat {A}_0$ the wave amplitude envelope, $a_0$ its amplitude, $\hat {A}_0$ a non-dimensional envelope, $\omega _0$ the carrier wave frequency and $k_0$ the carrier wavenumber. Where complex fields are given, the real part is understood, and $\varphi = k_0 x- \omega _0 t$. The first three rows are first-order solutions, valid for regular waves or wave packets. The remaining rows comprise second-order solutions for the wave-averaged Eulerian and Stokes velocities and the set-down. The second-order wave-averaged Eulerian velocity only arises for wave packets, considered in the experiments in Appendix B.

Figure 3

Figure 3.For viscous drag, magnitudes of the first-order horizontal motion amplification $X^{(1)}$ (a) and the variable submergence $\mathcal {S}^{(1)}$ (b) as functions of dimensionless object size $D/\lambda _0$ for different density ratios $\beta =\rho _o/\rho _f$, where the density ratio for each colour is shown in the legend. We have set $C_m= \beta /2$. Numerical and analytical solutions from perturbation theory are denoted by crosses and solid lines, respectively.

Figure 4

Figure 4.For viscous drag, arguments of the first-order horizontal motion amplification $X^{(1)}$ (a) and the variable submergence $\mathcal {S}^{(1)}$ (b) as functions of dimensionless object size $D/\lambda _0$ for viscous drag and for different density ratios $\beta =\rho _o/\rho _f$, as shown in the legend. We have set $C_m= \beta /2$. Numerical and analytical solutions from perturbation theory are denoted by crosses and solid lines, respectively.

Figure 5

Figure 5.For viscous drag, wave-induced drift amplification $X^{(2)}$ as a function of dimensionless object size $D/\lambda _0$ for different density ratios $\beta =\rho _o/\rho _f$ (see legend). We have set $C_m= \beta /2$. Numerical and analytical solutions from perturbation theory are denoted by crosses and solid lines, respectively.

Figure 6

Figure 6.For viscous drag, contributions to the wave-induced drift amplification $X^{(2)}$ from the five components in (3.20) as a function of non-dimensional object size $D/\lambda _0$ for density ratio $\beta =0.8$ and $C_m= \beta /2$.

Figure 7

Figure 7.Schematics of the object trajectory (red) and free surface (blue) for three cases: no variable submergence, variable submergence with no normal drag and variable submergence with normal drag. The schematics illustrate the physical mechanism for increased drift arising from variable submergence $s^{(1)}$, where variable submergence and drag are in the $n$-direction, and a mean motion in the $x$-direction is created due to the slope of the free surface $\partial _x\eta ^{(1)}$. For this illustration, we have chosen a density ratio $\beta =1/2$.

Figure 8

Figure 8.Laboratory-scale numerical simulation results using non-viscous drag for magnitudes of the first-order horizontal motion amplification $X^{(1)}$ (a) and the variable submergence $\mathcal {S}^{(1)}$ (b) as functions of dimensionless object size $D/\lambda _0$ for different density ratios $\beta =\rho _o/\rho _f$, where the density ratio corresponding to each colour is listed in the legend. Here, $C_m= \beta /2$. Numerical and analytical solutions from perturbation theory are denoted by crosses and solid lines, respectively.

Figure 9

Figure 9.Laboratory-scale numerical simulation results using non-viscous drag for wave-induced drift amplification $X^{(2)}$ as a function of dimensionless object size $D/\lambda _0$ and for different density ratios $\beta =\rho _o/\rho _f$ (see legend). Here, $C_m=\beta /2$. Analytical solutions using viscous drag from perturbation theory are denoted by solid lines.

Figure 10

Figure 10.Field-scale numerical simulation results using non-viscous drag for magnitudes of the first-order horizontal motion amplification $X^{(1)}$ (a) and variable submergence $\mathcal {S}^{(1)}$ (b) as functions of dimensionless object size $D/\lambda _0$ for different density ratios $\beta =\rho _o/\rho _f$, where the density ratio corresponding to each colour is shown in the legend. Field scale here denotes a $0.2\ \textrm {Hz}$ wave with a steepness of $\alpha =0.05$. Here, $C_m= \beta /2$. Numerical and analytical solutions from perturbation theory are denoted by crosses and solid lines, respectively.

Figure 11

Figure 11.Field-scale numerical simulation results using non-viscous drag for the wave-induced drift amplification $X^{(2)}$ as a function of dimensionless object size $D/\lambda _0$ for different density ratios $\beta =\rho _o/\rho _f$ (see legend). Field scale is modelled by a $0.2\ \textrm {Hz}$ wave with a steepness of $\alpha =0.05$. Here, $C_m=\beta /2$. Analytical solutions using viscous drag from perturbation theory are denoted by solid lines.

Figure 12

Figure 12.Experimental set-up used to track the motion of floating objects under wave motion generated by a double-element piston-type wave maker at the COAST Laboratory, University of Plymouth, UK.

Figure 13

Table 2.Matrix of experiments listing dimensional object diameter $D$, object density $\rho _o$, non-dimensional object diameter $D/\lambda _0$ and density ratio $\beta = \rho _o /\rho _f$.

Figure 14

Figure 13.Time histories of object horizontal position for each experiment. Each panel shows the five repeated experiments in different colours.

Figure 15

Figure 14.Magnitude of the first-order motion as a function of non-dimensional object size $D/\lambda _0$ for different density ratios (see legend): analytical solution with viscous drag (solid lines) and experiments (circles). The density ratios for the numerical solutions are listed in the legend; density ratios for the experiments are labelled using the same colour scale. The error bars are obtained from repeated experiments and correspond to two standard deviations.

Figure 16

Figure 15.Sub-harmonic horizontal object velocity relative to the Eulerian mean flow, normalised by the Stokes drift at the centre of the wave packet: $X^{(2)}_{{exp}}=(v_x^{(2)|_{t=0}}-u_x^{(2)}|_{t=0})/(u_{{s}}|_{t=0})$ where $u_{{s}}|_{t=0}=\omega _0 k_0 a_0^2$. The mean of the five repeated experiments is shown as a continuous red line, and the confidence band corresponding to two standard deviations is shaded in grey, with five lines overlaid for each individual experiment.

Figure 17

Figure 16.Second-order drift amplification factor $X^{(2)}$ as a function of non-dimensional object size for different density ratios (see legend): analytical solution with viscous drag (solid lines) and experiments (circles). The density ratios for the numerical solutions are listed in the legend; density ratios for the experiments are labelled using the same colour scale. The error bars are obtained from repeated experiments and correspond to two standard deviations.

Figure 18

Figure 17.Numerical predictions of the magnitude of the first-order horizontal motion amplification $X^{(1)}$ (a) and the variable submergence $\mathcal {S}^{(1)}$ (b) as functions of dimensionless object size $D/\lambda _0$ for non-viscous drag and for different density ratios $\beta =\rho _o/\rho _f$ (see legend). In the figure, periodic waves are denoted by crosses and wave packets of the same bandwidth as in the experiments by circles.

Figure 19

Figure 18.Numerical predictions of the magnitude of the second-order horizontal motion amplification $X^{(2)}$ as functions of dimensionless object size $D/\lambda _0$ for non-viscous drag and for different density ratios $\beta =\rho _o/\rho _f$ (see legend). In the figure, periodic waves are denoted by crosses and wave packets of the same bandwidth as in the experiments by circles.

Figure 20

Figure 19.Trajectory of a perfectly Lagrangian tracer obtained using a numerical solution of the present model with forcing provided by (D1). Panels (a,b) display the horizontal and vertical motions $x_p(t)$ and $z_p(t)$, with the blue dashed line showing the theoretical Stokes drift displacement and the red lines the superimposed wave amplitudes. Panels (c,d) show the tracer particle positions in the ($n,\tau$)-coordinate system.

Figure 21

Figure 20.The effect of alternative drag formulations on the numerical predictions of first-order variable submergence $S^{(1)}$ (a) and second-order drift $X^{(2)}$ (b) as a function of non-dimensional object size $D/\lambda _0$ for a density ratio $\beta =0.8$ at laboratory-scale conditions. The lines correspond to different drag formulations, labelled in the legend, using either viscous drag ($C_d= 24/Re$, solid lines), non-viscous drag ($C_d=C_d(Re)$, dashed lines) or turbulent drag ($C_d=1/2$, dotted lines), which either vary with the time-varying projected area in the respective directions ($\boldsymbol {A}(t)=\boldsymbol {A}_{{PA}}(t)$), with the constant projected area in the respective directions ($\boldsymbol {A}=\boldsymbol {A}_{{PA}}^{(0)}$), or with the submerged surface area (${A}(t)={A}_{{SA}}(t)$).

Figure 22

Figure 21.The effect of alternative added-mass formulations on the numerical predictions of first-order variable submergence $S^{(1)}$ (a) and drift $X^{(2)}$ (b) as a function of non-dimensional object size $D/\lambda _0$ for a density ratio $\beta =0.8$ at laboratory-scale conditions for non-viscous drag. The lines correspond to different added-mass formulations, described in the legend, with solid lines for directionally independent added-mass formulations, and dashed lines for added-mass formulations decomposed into normal and tangential directions.