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Quantitative Prediction of Segregation at Process Scale

Liu, Siying (2019) Quantitative Prediction of Segregation at Process Scale. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Segregation, or the separation/stratification of particles with differing properties, can lead to significant handling problems, product non-uniformity, and even complete batches being discarded at huge financial loss in multiple industries. Thus, one could argue that segregation is one of the most important factors in industrial processing of granular materials. There has been a tremendous focus in recent years on granular segregation problems and much has been learned about the mechanisms driving those phenomena. Segregation model development holds promise for translation of academic research into industrial practice; however, experimental validation of dynamic models is extremely difficult and typical segregation models are not inherently built with scale-up in mind. One unique aspect of our work is that we overcome these experimental limitations by exploiting a novel framework for segregation testing based on establishing an “equilibrium” between mixing and segregation 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 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 have introduced a new way of structuring segregation rate models that make them inherently more scalable and accurate for industrial use than any models previously reported. Types of segregation properties studied in this research include density, size, wet and shape. Our results suggest that one can prescribe (or design) industrial operating conditions that will lead to dramatically lower segregation extents.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Liu, Siyingsil32@pitt.edusil32
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairMcCarthy, Joseph
Committee MemberNiepa, Tagbo
Committee MemberVelankar, Sachin
Committee MemberRobertson, Anne
Date: 24 January 2019
Date Type: Publication
Defense Date: 16 November 2018
Approval Date: 24 January 2019
Submission Date: 7 November 2018
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 135
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Chemical and Petroleum Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Particle Technology, solid transport, Segregation
Date Deposited: 24 Jan 2019 15:42
Last Modified: 24 Jan 2019 15:42

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