Classification of granular materials via flowability-based clustering with application to bulk feeding
2020 Torres-Serra et al. - Classification of granular materials via flowability-based clustering with application to bulk feeding.pdf (1,263Mb) (Restricted access) Request copy
Què és aquest botó?
Aquest botó permet demanar una còpia d'un document restringit a l'autor. Es mostra quan:
- Disposem del correu electrònic de l'autor
- El document té una mida inferior a 20 Mb
- Es tracta d'un document d'accés restringit per decisió de l'autor o d'un document d'accés restringit per política de l'editorial
Rights accessRestricted access - publisher's policy (embargoed until 2023-01-22)
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
Feeder selection impacts the performance of bagging machinery throughout its life cycle, and yet it is usually based on qualitative assessments of flowability. We propose a data analysis methodology aimed at verifying the feeder-type classification of powders and grains by cluster analysis on their material properties. Results for a first data set of conventional properties show the granular materials clustered into as many groups as main bulk feeding systems. Mismatch between feeder classes and flowability-based clusters is explained by common industrial practice and incomplete material characterisation. For this reason, we introduce a set of specialised properties measured with the granular flow tester we have recently developed. Results for principal component analysis on a second extended property data set show that similarly flowing granular materials are better detected considering the specialised properties. This research contributes to objectify the decision-making process of bulk feeder selection from the quantitative description of granular flow.
© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
CitationTorres-Serra, J.; Rodriguez-Ferran, A.; Romero, E. Classification of granular materials via flowability-based clustering with application to bulk feeding. "Powder technology", 22 Gener 2021, vol. 378, núm. A, p. 288-302.
|2020 Torres-Ser ... cation to bulk feeding.pdf||1,263Mb||Restricted access|