Segregation model development holds promise for translation of academic research into industrial
practice. One significant hindrance to model development, however, is the inherent difficulty
in measuring segregation rates (especially in an experimental setting). In this project, we seek
to establish an “equilibrium” between segregation and flow perturbation in free surface granular
flows in order to overcome this experimental hurdle. That is, by using periodic flow inversions,
we hope to alter the steady-state distribution of particles whereby there exists a balance between
the rate of segregation and the perturbation rate. In this way, we can combine the segregation
rate expressions that we are interested in testing with our previously developed segregation control
framework such that knowing the perturbation rate, we can deduce the segregation rate (much
like knowing an equilibrium concentration, along with a reverse reaction rate, one can deduce the
rate of the forward reaction). In our first year, we examined binary segregation rate models, both
computationally and experimentally, that are appropriate for free surface flows of granular materials.
We started with well established models for both size segregation and density segregation and
compare these to new and proposed models. We tested these models, both computationally and
experimentally, using an industrially-relevant device – a tumbler-type mixer – by introducing an
axially-located baffle that periodically perturbs the flow. This flow perturbation allows us to modify
the expected segregation “equilibrium” such that varying flow properties (like rotation rate) as
well as material properties (like size or density ratio) will lead to results that collapse onto a “master
curve” when using an accurate segregation model. As the project progresses, (experimentally)
validated segregation models can be incorporated into device-level transport equations in order to
yield quantitative prediction of segregation at process scale.