<p></p><p>Granular
material blending plays an important role in many industries ranging from those
that manufacture pharmaceuticals to those producing agrochemicals. The ability
to create homogeneous powder blends can be critical to the final product
quality. For example, insufficient blending of a pharmaceutical formulation may
have serious consequences on product efficacy and safety. Unfortunately, tools for
quantitatively predicting particulate blending processes are lacking. Most
often, parameters that produce an acceptable degree of blending are determined
empirically.</p>
<p> </p>
<p>The
objective of this work was to develop a validated model for predicting the
magnitude and rate of granular material mixing and segregation for binary mixtures of granular material in systems of industrial
interest. The model utilizes
finite element method simulations to determine the bulk-level granular velocity
field, which is then combined with particle-level diffusion and segregation correlations
using the advection-diffusion-segregation equation. </p>
<p> </p>
<p>An
important factor to the success of the finite element method simulation used in
the current work is the material constitutive model used to represent the
granular flow behavior. In this work, the Mohr-Coulomb elastoplastic (MCEP) model
was used. The MCEP model parameters were calibrated both numerically and
experimentally and the procedure is described in the current work.
Additionally, the particle-level diffusion and segregation correlations are
important to the accurate prediction of mixing and segregation rates. The
current work derived the diffusion and segregation correlations from published literature and determined a methodology for obtaining the particle
diffusion and segregation parameters from experiments.</p>
<p> </p>
<p>The
utility of this modelling approach is demonstrated by predicting mixing
patterns in a rotating drum and Tote blender as well as segregation patterns in
a rotating drum and during the discharge of conical hoppers. Indeed, a significant advantage
of the current modeling approach compared to previously published models is
that arbitrary system geometries can be modeled.</p>
<p> </p>
<p>The model
predictions were compared with both DEM simulation and experiment results. The model is able to quantitatively
predict the magnitude and rate of powder mixing and segregation in two- and three-dimensional
geometries and is computationally faster than DEM simulations. Since the numerical approach does not
directly model individual particles, this new modeling approach is well suited for predicting mixing
and segregation in large industrial-scale systems.</p><br><p></p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/7590959 |
| Date | 10 May 2019 |
| Creators | Yu Liu (5930003) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/Modeling_Granular_Material_Mixing_and_Segregation_Using_a_Finite_Element_Method_and_Advection-Diffusion-Segregation_Equation_Multi-Scale_Model/7590959 |
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