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Depth-integrated equations for entraining granular flows in narrow channels

Published online by Cambridge University Press:  30 January 2015

H. Capart*
Affiliation:
Department of Civil Engineering and Hydrotech Research Institute, National Taiwan University, Taipei 106, Taiwan
C.-Y. Hung
Affiliation:
Department of Civil Engineering and Hydrotech Research Institute, National Taiwan University, Taipei 106, TaiwanLamont-Doherty Earth Observatory of Columbia University, Palisades, New York, USA
C. P. Stark
Affiliation:
Lamont-Doherty Earth Observatory of Columbia University, Palisades, New York, USA
*
†Email address for correspondence: hcapart@yahoo.com
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Abstract

Flowing over erodible beds, channelized granular avalanches can alter their volume by entraining or detraining basal grains. In detail, entrainment results from a gradual adjustment of stress and velocity profiles over depth, bringing bed material past yield (and vice versa for detrainment). To capture this process, we propose new depth-integrated equations that balance kinetic energy in addition to mass and momentum. The equations require a local granular rheology, assumed viscoplastic, but no extra erosion law. Entrainment rates are instead deduced from the depth-integrated layer dynamics. To check the approach, we obtain solutions for non-equilibrium heap flows, and compare them with experiments conducted in a seesaw channel.

Information

Type
Rapids
Copyright
© 2015 Cambridge University Press 
Figure 0

Figure 1.Channelized granular flows over erodible beds: (a) variable definitions and velocity distribution for a typical granular column; (b) evolving profiles for a generic space- and time-varying flow; (c) the seesaw channel configuration used to produce transient uniform flows.

Figure 1

Figure 2.Phase portrait for transient heap flows showing generic system trajectories (light grey curves) and three typical trajectories (blue, red, green) started from stationary states at rest, milder and steeper inclination (initial conditions on locus $h_{\ast }=\overline{u}_{\ast }^{2/5}$, black line). Light grey shading delineates the sector where both variables, $\overline{u}_{\ast }(t)$ and $h_{\ast }(t)$, evolve monotonically.

Figure 2

Figure 3.Velocity profiles for transient heap flows: (a–c) profiles at intervals ${\rm\Delta}t_{\ast }=0.1$ calculated using the depth-integrated theory (lines) and the full local equations (dots); (d–f) profiles at intervals ${\rm\Delta}t=0.12~\text{s}$ measured from seesaw experiments of target inclinations ${\it\beta}_{2}=0.479,0.473$ and 0.450. The predicted equilibrium profiles are shown in black.

Figure 3

Figure 4.Time-evolving layer variables for transient heap flows started from rest (blue), from a slower stationary state (red) and from a faster stationary state (green): (a) depth-integrated kinetic energy $k_{\ast }$; (b) momentum $q_{\ast }$; (c) surface velocity $\widetilde{u}_{\ast }$; (d) depth $h_{\ast }$. The bold lines are the predictions from the depth-integrated theory and the thin lines are the experimental measurements, apart from the inset of (d) where the thin line is the depth calculated numerically from the full local equations.