Abstract
We formulate and solve a model problem of dispersion of dense granular materials in rapid shear flow down an incline. The effective dispersivity of the depth-averaged concentration of the dispersing powder is shown to vary as the Péclet number squared, as in classical Taylor–Aris dispersion of molecular solutes. An extension to generic shear profiles is presented, and possible applications to industrial and geological granular flows are noted.
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Notes
For the laboratory-scale chute flow from [18], \(\ell \simeq 1\) m, so \(h^2/D_0\simeq 10^2\) s and \(\ell /\overline{v_x}\simeq 1\) s. In this particular experimental setup, we would not expect to see dispersion because the granular layer is too thin, and the device is too short in the streamwise direction.
For molecular solutes, streamwise variations of the layer thickness of the form \(h(z) = h_0[1+\beta f(z)]\) have been shown to lead to contributions on the order of \(\beta ^2\) to the effective dispersivity \(\fancyscript{D}\) [23]. Hence, streamwise variations of the layer could be incorporated into the dispersion calculation, by replacing \(h\) with \(h(z)\) everywhere, without changing the result, as long as the variations are small, i.e., \(\beta = \fancyscript{O}(h_0/\ell ) \ll 1\), which renders the \(\fancyscript{O}(h_0^2/\ell ^2)\) contributions to \(\fancyscript{D}\) negligible within the chosen order of approximation (see the “Appendix”). Furthermore, we expect that the Bagnold profile remains valid for such \(h(z)\) with \(\beta \ll 1\).
That is, the proportion of volume occupied by the number of particles in a unit area. Note that \(c\) is the concentration of the injected or “tagged” particles while \(\phi \) is the volume fraction of the granular material, i.e., all particles present in a unit area, not just tagged ones.
By the linearity of Eq. (2), \(c_0\) is arbitrary. For definiteness, it can be taken to be, e.g., \(c_0 = \int _{-\infty }^{+\infty } \bar{c}(x,0) \,\mathrm{d} x\) for a finite-mass initial condition.
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Acknowledgments
I.C.C. was supported by the National Science Foundation (NSF) under Grant No. DMS-1104047 (at Princeton University) and by the LANL/LDRD Program through a Feynman Distinguished Fellowship (at Los Alamos National Laboratory). LANL is operated by Los Alamos National Security, L.L.C. for the National Nuclear Security Administration of the U.S. Department of Energy under Contract No. DE-AC52-06NA25396. H.A.S. thanks the NSF for support via Grant No. CBET-1234500. We acknowledge useful discussions with Ian Griffiths and Gregory Rubinstein on the derivation of the dispersion equations for the case of non-constant diffusivity, and we thank Ben Glasser for helpful conversations.
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Appendix
Appendix
Following [2, 20], first we substitute \(c(x,z,t) \equiv \bar{c}(x,t) + c'(x,z,t)\) and \(v_x(z) \equiv \overline{v_x} + v_x'(z)\) into Eq. (1) to obtain
Next, we apply the depth-averaging operator \(\overline{(\cdot )} = \frac{1}{h}\int \nolimits _0^h (\cdot ) \,\mathrm{d}z\) to Eq. (18) to obtain the governing equation for the depth-averaged concentration:
where the average of the last term on the right-hand side of Eq. (18) vanishes due to the no-flux boundary condition \(\partial c/\partial z = 0\) (\(\Rightarrow \partial c'/\partial z = 0\)) at \(z=0,h\). In Eq. (19) and below, the double-underlined terms turn out to be the dominant ones in the dispersion regime. Now, we subtract Eq. (19) from Eq. (18) to obtain the governing equation for the concentration fluctuations:
At this point, we invoke the asymptotic assumptions in the dispersion regime, namely that \(|c'| \ll \bar{c}\) once transverse diffusion has equilibrated, i.e., for \(\ell /h\gg \overline{v_x}h/D_0\). Meanwhile, both \(\overline{v_x}\) and \(v_x'\) are the same order of magnitude because the velocity field is steady and given. Thus, the scales for the various variables are
where \(0<\varepsilon \ll 1\), and the scaling for \(z\) is set by the assumption \(\ell /h \gg \overline{v_x}h/D_0\), which implies that \(h \ll \ell [D_0/(\overline{v_x} h)]\), where \(D_0/(\overline{v_x} h)\) is the inverse of the (dimensionless) Péclet number, which is assumed to be \(\fancyscript{O}(1)\).
Now, to ensure that the dispersion problem is nontrivial, both the material derivative and the fluctuation term on the left-hand side of Eq. (19) should be retained, which sets the timescale to be \([t] = \ell /(\varepsilon U)\), i.e., we are considering the “long time” behavior as posited by Taylor [2]. Then, upon dividing both sides of Eq. (19) by \(\varepsilon c_0 U/\ell \) and defining \(U h/D_0 = \fancyscript{O}(1)\) as the Péclet number, it is evident that the first term on the right-hand side of Eq. (19) (underlined) is \(\fancyscript{O}(1)\), while the second term is \(\fancyscript{O}(\varepsilon )\). Thus, in the dispersion regime, the evolution equation (19) of the depth-averaged concentration reduces to Eq. (2).
Turning to the left-hand side of Eq. (20), we first divide both sides by \(c_0 U/\ell \). Then, it is clear only the second term on the left-hand side (double underlined) is \(\fancyscript{O}(1)\), while all other terms are \(\fancyscript{O}(\varepsilon )\) or smaller. Meanwhile, on the right-hand side of Eq. (20), again defining \(U h/D_0 = \fancyscript{O}(1)\) as the Péclet number, only the second-to-last term (double underlined) is \(\fancyscript{O}(1)\), while all other terms are \(\fancyscript{O}(\varepsilon )\) or smaller. Thus, in the dispersion regime, the evolution equation (20) of the concentration fluctuations reduces to Eq. (3).
Finally, we note that Eqs. (2) and (3) can also be derived formally by perturbation techniques such as the method of multiple time scales [42, 43] with the aspect ratio \(\varepsilon \equiv h/\ell \) as the small parameter.
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Christov, I.C., Stone, H.A. Shear dispersion in dense granular flows. Granular Matter 16, 509–515 (2014). https://doi.org/10.1007/s10035-014-0498-0
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DOI: https://doi.org/10.1007/s10035-014-0498-0