Identification of Optimal Mill Operating Parameters during Grinding of Quartz with the Use of Population Balance Modeling

Abstract

It is known that ball milling is an energy intensive process and great efforts have been made over the years to improve energy efficiency. The use of population balance models (PBMs) can assist in the design of mineral processing circuits and the scale-up of laboratory mill results to full-scale. However, since each model has its own capabilities and limitations, it is believed that a combined use will provide more accurate information for the reliable description of the process. In this study, the simulation of grinding of quartz is investigated in order to identify the optimal mill operating parameters. With the use of population balance modeling the specific rate of breakage and the cumulative breakage parameters can be determined from mono-size, short grinding time batch tests. The determined breakage parameters were back calculated by minimizing the residual error between experimental and reproduced size distributions. By combining two software packages the back calculated breakage parameters were used for the prediction of the optimum ball filling volume. The proposed procedure can be also applied for the identification of optimal mill operating parameters for other minerals.

Improved Modeling of the Grinding Process through the Combined Use of Matrix and Population Balance Models

“…Also, from the same table, it is seen that for the same material the value of α T increases when U decreases and this suggests that grinding is more effective at lower U values. However, a recent study has shown that there is an optimum value of U for which the breakage rate obtains the maximum value and grinding becomes more efficient [30]. Table 3.…”

“…These functions define the fundamental size-mass balance equation for fully mixed batch grinding operations. Many researchers have underlined the advantages of these functions [26][27][28], while the scale-up from laboratory to industrial mills has also been discussed in a number of recent studies [1,[29][30][31][32]. Furthermore, several studies investigated the effect of the variation of kinetic model parameters, when different mill operating conditions were used.…”

Grinding Kinetics of Slag and Effect of Final Particle Size on the Compressive Strength of Alkali Activated Materials

“…Slag, prior to its use in most applications, requires grinding which is an energy intensive process, characterized by high CO 2 emissions and increased processing cost. In addition, grinding is a low-efficiency process because a large share of the consumed energy is absorbed by the device and only a small part is used for size reduction [21,22]. Considering these factors, the investigation of grinding kinetics of any raw material, including slag, is an important aspect.…”

Correlation between Material Properties and Breakage Rate Parameters Determined from Grinding Tests

“…It is mentioned that the breakage rate parameters were back calculated using the Moly-Cop Tools™ v.1.0 software and the determined values are presented in Table 5. The back calculation method is described in detail in a previous recent publication of the authors [8]. …”

“…Scientific research, aiming to improve grinding efficiency, was initiated with the empirical relationships of Rittinger, Kick, Bond as well as Walker and Shaw, which described the energy-particle size relationship [8]. Later, theories which incorporated the concept of particle size distribution were developed [9,10], while recently research focused on the use of the mechanistic approach which is based on the recognition of physical events that take place during grinding [11][12][13].…”