Prediction of average shape values of quartz particles by vibrating disc and ball milling using dynamic image analysis based on established time-dependent shape models

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Ulusoy U., Bayar G.

PARTICULATE SCIENCE AND TECHNOLOGY, cilt.40, sa.7, ss.870-886, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 40 Sayı: 7
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1080/02726351.2022.2042879
  • Dergi Adı: PARTICULATE SCIENCE AND TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), Chemical Abstracts Core, Communication Abstracts, Compendex, Computer & Applied Sciences, EMBASE, INSPEC, Metadex, Pollution Abstracts, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.870-886
  • Anahtar Kelimeler: Quartz, shape, dynamic image analysis, circularity, vibratory disc mill, ball mill, SIZE DISTRIBUTION, LABORATORY BALL, FLOTATION, KINETICS, MINERALS, REMOVAL, CALCITE, IRON, TALC, ORE
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

Although grinding kinetics has been the subject of many researches, there is no research examining the shape kinetics of particles ground by different mills using dynamic image analysis (DIA) in the literature. In this investigation, how the shapes of quartz particles change over time at two different size fractions in two different mills is modeled using the latest image analysis technique, since particle shape of mineral is important in flotation and hydraulic fracturing processes. Empirical time-dependent shape models based on the correlation between average circularity (C-av(.)) and bounding rectangle aspect ratio (BRAR(av.)) parameters and grinding time for vibratory disc mill and ball milled particles are established with high R-2 values by different fitting. Furthermore, average shape values of particles ground by the mills depending on grinding time were predicted for two size fractions. It was found that, C-av. data can be better described by linear fitting equations, on the other hand BRAR(av.) data can be better represented by power fitting equations. Since predicted and measured shape values were found close to each other, this approach provides useful information for estimating the milling time required to produce the particles by milling (with less energy and cost) appropriately for intended use.