4.7 Article

Modelling of the detachment of adhesive dust particles during bulk solid particle impact to enhance dust detachment functions

期刊

POWDER TECHNOLOGY
卷 400, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.powtec.2022.117238

关键词

Discrete element method (DEM); Adhesive forces; Dust detachment functions; Dust emissions

资金

  1. association Forschungs-Gesellschaft Verfahrens-Technik e.V. [IGF 20974N]
  2. Federal Ministry for Economic Affairs and Climate Action through the German Federation of Industrial Research Associations (AiF)

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This study investigates the detachment of fine adhered dust particles during bulk particle contacts using an adhesive Discrete Element Method (DEM). The research introduces dust detachment functions in a non-adhesive DEM, which track only the coarse carrier particles as a composed bulk particle. The implemented detachment functions, including normal and tangential lift-off conditions, as well as a rotational condition, are benchmarked based on dust-resolved adhesive DEM simulations.
The detachment of fine adhered dust particles during bulk particle contacts is studied with an adhesive Discrete Element Method (DEM) to describe the carrier and the dust particle motion. Further, dust detachment functions are realized in a non-adhesive DEM, in which only the coarse carrier particles are tracked as one composed bulk particle. The implemented detachment functions include three criteria, a normal and a tangential lift-off condi-tion as well as a rotational condition. These functions are benchmarked based on dust-resolved adhesive DEM simulations by varying crucial parameters in the course of particle-particle and particle-wall contacts. In advance, the adhesive force is calibrated using experimental single drop tests. The detachment criteria reflect the physical detachment of individual dust particles well assuming dust particles with a narrow size distribution. The appli-cation of the enhanced dust detachment functions therefore allows to predict dust release of individual dust par-ticles with significantly less computing time.(c) 2022 Elsevier B.V. All rights reserved.

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