PREDICTING SCREENING AND CLASSIFICATION PRODUCTS VIA THE PSEUDORANDOM NUMBER SELECTION ROUTINE

Screening and classification are performed for the separation of particles by their sizes. There empirical, phenomenological, numerical models predicting size distributions screening/classification products. This paper introduces a new algorithm same purpose, which partially mimics phenomenological models. The iteratively selects monosize fractions with pre-defined probabilities, then carries particle masses from selected either to oversize or undersize product. applicability was validated against product some industrial-scale operations provided in literature. results show that is predictive if each has selection probability proportional mass its fraction power diameter. Results also suggest vibrating screens can provide sharpest separation.