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Journal Club Theme of July 2013: Predicting granular flows: A new size-dependent constitutive model

Ken Kamrin's picture

Since Coulomb initiated the topic over 200 years ago, continuum modeling of granular materials has remained an infamously difficult subject. Granular matter is common in everyday life (soil, sand, food grains, pharmaceuticals, etc) and second only to water as the most handled type of industrial material. However, a predictive, general constitutive relation for granular flow is lacking. This has become an expensive world-wide setback, since geotechnical and industrial flows are often on space- and time-scales too large for discrete particle simulation. It begs us to ask: Is there any hope for a "Navier-Stokes" equivalent for sand?  With a view toward this question, in this journal club entry I'll outline some encouraging recent results based on a new model obtained with collaborators Georg Koval (of INSA Strasbourg) and recently-former postdoc David Henann (just started as Mech E faculty at Brown). See papers [1] and [2] for full details.

Throughout, we limit the discussion to well-developed flows, in order to make the problem more tractable. This focus is part of a bigger strategy --- once we understand the well-developed state, it instructs the long-time behavior when developing critical-state-like models for the transients.


 

Inertial (local) rheology

Our story begins in the mid-2000's, with the advent of the inertial rheology for granular flow, developed by a group of southern French researchers [3,4]. As reported in my prior journal club entry, the premise of the model can be extracted logically from dimensional arguments in a simple shear cell (see notational details below). In the end, for a given quasi-monodisperse granular composition, the result is a local rheology of the form

simple shearing

 

 

 

 

 

 

 

Of note, the function f is empirically fit and demonstrates a clear yield criterion; f = 0 if τ/P = μ < μs for material parameter μs. The inertial rheology above has shown to work extremely well for steady-state, homogeneous simple shear flows.

To broaden beyond simple shear, the relation can be written tensorially (i.e. presuming codirectionality and the Drucker-Prager yield surface), and instituted in general geometries as a 3D viscoplastic rheology [4], or as the flow rule in an elasto-viscoplastic rheology [5]. While these extensions give reasonable results for rapid flows, trouble quickly sets in.

Despite how well the inertial rheology may work in homogeneous simple shear, it fails for slow non-uniform flows, even ones where the steady flow profile is locally simple shearing everywhere (say, annular shear flow) [6]. Of note, the model predictions tend to under-predict the size of flow features; rather, it happens that the grain size itself plays the key role in determining the width of such features. Moreover, we see creeping flow occurring in regions where stress levels are well beneath the μs value obtained from uniform simple shearing, as long as a flow gradient is present. These are tell-tale signs of nonlocality, set by a length-scale associated to the particle size, and consequently, well-developed granular rheology must be recast with nonlocal (or gradient-based) constitutive modeling. Since grains are commonly on our size-scale, the consequences of the nonlocality can be appreciated and noticed with the naked eye, in a truly remarkable fashion. Indeed one does not have to try hard to produce a flow where almost the entire profile is due to size-effects, and differs completely from the inertial rheology prediction.

 

Extending to a nonlocal flow rule

Our model, the Nonlocal Granular Fluidity (NGF) model, aims at resolving these issues, and can be backed out statistically from a micro-mechanism in which "flow aids flow" [7]. That is, a microscopic rearrangement event at some location can emit stress perturbations that affect material some distance away. Hence, in the continuum limit, it is both the mean applied stress and disturbances from neighboring flow (in the form of a Laplacian term scaled by the particle size) that together determine the shear-rate at some point. Mathematically, NGF resembles an implicit gradient theory, e.g. [8]. Omitting mathematical specifics here (see [2] for details), we note the following important features of the model:

1) NGF couples the stress/strain-rate relation to a scalar field, the "granular fluidity", which satisfies a PDE calling on the grain-size.

2) NGF reduces to the inertial relation in the absence of flow gradients (as it should).

3) NGF necessitates only one new material parameter; an order-one dimensionless constant we call A, the nonlocal amplitude. The other parameters are borrowed directly from the inertial rheology. In total, NGF uses three material parameters.

 

Results

The combined results of [1] and [2] show that the NGF model predicts flow and stress fields with a newfound level of accuracy, as verified over hundreds of geometries.

Our initial demonstrations in [1] were in the simplest 2D geometries --- flow in an annular cell, gravity-driven flow down a vertical chute, and dragging of a plate over granular bed. Its predictions matched data from discrete simulations of disk flows (c/o Georg Koval) in the analogous geometries for various different values of system size or gravity, over many orders of magnitude in flow speed. A single calibration of the material parameters was used throughout.

With the success of the 2D prototype cases, the model was recast in 3D, and an Abaqus User-Element was created (c/o David Henann) to permit us to solve the NGF system in arbitrary 3D geometries [2]. We re-calibrated the model parameters for quasi-monodisperse 3D glass beads, and compared model predictions against experimental data for bead flows in many geometries. As a stringent test, we first compared NGF predictions in "split-bottom" flow geometries, a family of flow environments made famous over the last decade for having resisted all previous continuum models. It was shown in [2] that NGF is the first continuum model to quantitatively capture all features of the flows in these geometries. For example, see below (from [2]).

 

split bottom cell

(a) A schematic of the split-bottom geometry: Grains fill an annular trough split along its bottom at radius Rs.  The outter portion is rotated while holding the inner portion fixed.  (b,c) Model predictions for the flow field as measured by the revolution rate ω(r,z) = νθ(r,z) / RΩ for different filling heights H.  Note the Heaviside profile at z=0 spreading out z increases. (d) Comparing the predicted flow field on the top surface (z=H) to experimental data [9] for various filling heights H.


 

We then applied the same model with same parameters in completely different flow environments and found equally high agreement with experimental data on glass bead flows, reflecting the geometric-generality of NGF. For example, see below (from [2]).

 

other flow environments

(Left) Comparison of NGF prediction (solid line) to experimental flow data (symbols) in a 3D, gravity-compacted annular shear apparatus [10]. (Right) Comparison of NGF prediction (solid line) to experimental flow data (symbols) in a 3D plate-dragging geometry in the presence of gravity [11].


 

More to do

Despite the encouraging results, there remain several questions to answer. For instance, there are lingering issues about the form of fluidity boundary conditions, how exactly to incorporate transient effects and/or anisotropy internal variables within this framework, and the exact connection between grain properties and the nonlocal amplitude A. Please see the end of our paper [2] for a comprehensive discussion of the major open issues.

Again, much appreciation to my collaborators Koval and Henann!

 

 


[1] Kamrin and Koval, Phys Rev Lett (2012)


[2] Henann and Kamrin, PNAS (2013)


[3] da Cruz et al, Phys Rev E (2005)


[4] Jop et al, Nature (2006)


[5] Kamrin, Int J Plasticity (2010)


[6] Koval et al, Phys Rev E (2009)


[7] Bocquet et al, Phys Rev Lett (2009)


[8] Anand et al, Int J Plasticity (2012)


[9] Fenistein and van Hecke, Nature (2003)


[10] Losert et al, Phys Rev Lett (2000)


[11] Siavoshi et al, Phys Rev E (2006)
 

Comments

Xuanhe Zhao's picture

Ken,

Many thanks for posting this interesting topic on granular materials. I still remember the interesting video on Mars Rover Opportunity wheels out of sand trap you showed to us the other day. Not really digging the field of granular physics/mechanics myself, I would like to ask a simple question. Can we regard the models presented here as viscoplastic models with microstructural parameters? Then, would the models developed for viscoplastic polymers shed any light on the development of constitutive models for granular materials?

Ken Kamrin's picture

Xuanhe,

"Digging" granular materials, eh?  Thanks for posting one of my favorite granular-related vids.  It's amazing how something as simple as sand can foil a NASA mission.

Yes, one could see the model presented here as a viscoplastic model with an internal variable. Unlike standard internal variable treatments, however, our variable does not evolve under a local calculation.  Rather ours is obtained as the solution of a PDE, which has the effect of correlating values of the internal variable with values in neighboring material.  The grain size is then the key micro-size for detemining the length of these correlations.

It is very possible there is a connection with amorphous ploymer modeling, given the amorphous commonaility.  Is there a particular model you have in mind?  That would be good to know.  I know some polymer flow models though I am less aware of those which may include a size-effect.

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