Pseudo-dynamic simulations applied to ball mill grinding circuit using population balance model and Monte Carlo Method

Abstract

Abstract Process simulations can be used to improve grinding circuit performance, which efficiently reduces operating costs. The population balance model (PBM) is widely accepted for grinding modeling because it can reproduce breakage events in tumbling mills, as described by Austin et al. (1984). In this study, a pseudo-dynamic model is introduced, integrating the PBM with the Monte Carlo Method to stochastically simulate variables in an industrial grinding circuit. This integrated approach enabled circuit simulations over a period of 2 hours, representing the operational variables as seen in historical data. Model validation showed a correlation of 0.74 in the product size distribution when comparing simulated outcomes with the original population.

Keywords

• comminution
• modeling
• stochastic process
• PBM
• MCM