Quantitative Prediction of Segregation at Process Scale

Publication Reference: 
ARR-68-02
Author Last Name: 
McCarthy
Authors: 
Joseph J. McCarthy
Report Type: 
ARR
Research Area: 
Powder Flow
Publication Year: 
2016
Publication Month: 
12
Country: 
United States

Executive Summary

Segregation model development holds promise for translation of academic research into industrial

practice. Two significant issues that hamper the applicability of models in industry, however,

are (1) the inherent difficulty in measuring segregation rates (especially in an experimental setting)

for validation purposes and (2) the significant dearth of validated scale-up studies for these models.

In this project, we seek to alleviate these two shortcomings of segregation research through a

combined theoretical, computational, and experimental program. One unique aspect of our work

is that we use flow perturbations to establish an “equilibrium” between segregation and mixing in

free surface granular flows in order to alter the steady-state distribution of particles. By achieving

this balance between the rate of segregation and the perturbation rate, we can combine the model

expressions that we are interested in testing with dramatically simplified experiments to ultimately

deduce the segregation rate (and validate the expressions). Moreover, by exploring a novel view

of the interplay between granular rheology and segregation, we aim to introduce a new way of

structuring segregation rate models that will make them inherently more scalable than any models

previously reported. As the project progresses, we expect to yield – either via adoption from the

literature or through new theoretical development – (experimentally) validated segregation models

that can be incorporated into device-level transport equations in order to supply quantitative

prediction of segregation at process scale.