On the determination of particle impact breakage in selection function--颗粒学报PARTICUOLOGY

Wang, L. G., Ge, R., & Chen, X. (2022). On the determination of particle impact breakage in selection function. Particuology, 65, 117-132. https://doi.org/10.1016/j.partic.2021.08.003

On the determination of particle impact breakage in selection function

Li Ge Wang ^{a b}, Ruihuan Ge ^b, Xizhong Chen ^{b c *}

a Process Systems Enterprise, Hammersmith, London, UK
b Department of Chemical and Biological Engineering, University of Sheffield, UK
c Process and Chemical Engineering, School of Engineering, University College Cork, Ireland

10.1016/j.partic.2021.08.003

Volume 65, June 2022, Pages 117-132

Received 11 January 2021, Revised 22 July 2021, Accepted 5 August 2021, Available online 30 August 2021, Version of Record 8 November 2021.

E-mail: Xizhong.chen@ucc.ie

Highlights

• Impact mode and breakage pattern of particles are summarized.

• Strengths and drawbacks of literature breakage models are scrutinized.

• Particle impact breakage probability is evaluated with unified criteria.

• A novel computational modelling workflow for a milling process is proposed.

• Selection functions are assessed with the value of digital twin highlighted.

Abstract

This paper presents a thorough study of particle impact breakage in selection function with a unified breakage criterion. The impact mode and breakage pattern for particulate materials are classified based on a significant review of well-established impact testers. It was found that the lack of a unified breakage criterion to determine the breakage probability disables a direct comparison of particle breakage propensity from different impact loading testers. The literature breakage models to describe the breakage probability are reviewed where the advantage and drawback of these models are scrutinized. The sourced literature breakage models are compared with the zeolite breakage datasets in a unified breakage criterion to evaluate the model performance. A novel computational modelling workflow for a milling process is proposed to provide a guidance in implementing the digital twin in milling process prediction. The breakage probability models, i.e. the selection functions are comprehensively assessed in population balance model to examine the model serviceability. The model simplicity and fidelity in the model assessment are specifically discussed and the value of digital twin in substantially reducing the experimental trials is highlighted.

Graphical abstract

Keywords

Impact breakage; Breakage criteria; Breakage model assessment; Selection function; Population balance model; Digital twin

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