Search

Your search keyword '"Gleiss, Marco"' showing total 20 results
Start Over Author "Gleiss, Marco" Publisher mdpi ag
20 results on '"Gleiss, Marco"'

4. Use of Multiscale Data-Driven Surrogate Models for Flowsheet Simulation of an Industrial Zeolite Production Process

Author

Skorych, Vasyl, primary, Buchholz, Moritz, additional, Dosta, Maksym, additional, Baust, Helene Katharina, additional, Gleiß, Marco, additional, Haus, Johannes, additional, Weis, Dominik, additional, Hammerich, Simon, additional, Kiedorf, Gregor, additional, Asprion, Norbert, additional, Nirschl, Hermann, additional, Kleine Jäger, Frank, additional, and Heinrich, Stefan, additional

Published
2022
Full Text
View/download PDF

11. Development of a New Solver to Model the Fish-Hook Effect in a Centrifugal Classifier

Author

Betz, Michael, Nirschl, Hermann, and Gleiss, Marco

Subjects
centrifugal air classifier, Chemical engineering, ddc:660, particle classification, CFD, Mineralogy, fish-hook, MPPIC, QE351-399.2
Abstract

Centrifugal air classifiers are often used for classification of particle gas flows in the mineral industry and various other sectors. In this paper, a new solver based on the multiphase particle-in-cell (MP-PIC) method, which takes into account an interaction between particles, is presented. This makes it possible to investigate the flow process in the classifier in more detail, especially the influence of solid load on the flow profile and the fish-hook effect that sometimes occurs. Depending on the operating conditions, the fish-hook sometimes occurs in such apparatus and lead to a reduction in classification efficiency. Therefore, a better understanding and a representation of the fish-hook in numerical simulations is of great interest. The results of the simulation method are compared with results of previous simulation method, where particle–particle interactions are neglected. Moreover, a validation of the numerical simulations is carried out by comparing experimental data from a laboratory plant based on characteristic values such as pressure loss and classification efficiency. The comparison with experimental data shows that both methods provide similar good values for the classification efficiency d50, however, the fish-hook effect is only reproduced when particle-particle interaction is taken into account. The particle movement prove that the fish-hook effect is due to a strong concentration accumulation in the outer area of the classifier. These particle accumulations block the radial transport of fine particles into the classifier, which are then entrained by coarser particles into the coarse material.

Published
2021

Catalog

Books, media, physical & digital resources
See catalog results