Investigating the effects of random sieving losses on particle size distributions


CAMALAN M.

PARTICULATE SCIENCE AND TECHNOLOGY, 2019 (SCI İndekslerine Giren Dergi) identifier identifier

Özet

Sieving analyses are very susceptible to the unavoidable particle losses. Therefore, it is important to assess how sieving losses will affect the particle size distributions. This study aims to simulate sieving losses under a computing environment to further investigate their effects on the particle size distributions. For the purpose of this study, the cumulative size distributions of different particulate materials were generated by using the Gates-Gaudin-Schuhmann (GGS) and Rosin-Rammler-Bennett (RRB) equations. Then, random sieving losses were generated by taking random mass fractions from randomly-selected size intervals. The sums of these random losses were subtracted from the original masses in the size intervals. The calculated residual masses in the size intervals were used to construct the cumulative size distributions of the residual materials. Results show that increasing the mass of sieving losses will only change the position of wide distributions. However, increasing losses will both change the position and shape of narrow distributions. Tolerating all sources of sieving errors may be better to preserve the distribution shapes. The simulation results suggest the rule-of-thumb limit for sieving losses. Sieving losses cause the GGS plots of the grinding products to deviate to bilinear shapes at finer size ranges.