Evaluation of material properties using planetary ball milling for modeling the change of particle size distribution in a gas-solid fluidized bed using a hybrid artificial neural network-genetic algorithm approach

Abstract

This study aims to use planetary ball-milling as an evaluation tool of material properties and the result is subsequently used to develop a model for the change in particle size distribution (PSD) during fluidization for a range of materials using artificial neural network (ANN) method. It is believed that material properties such as hardness, density, brittleness, structure, etc play a crucial role in the particle attrition behavior. Unfortunately, little information on material properties is available, considering the wide variety of materials present. As a result, planetary ball-milling is proposed as a fast assessment technique to identify the properties of different materials. Planetary ball milling devices are readily available in most laboratories and the reduction in PSD can resemble the particle attrition process during fluidization. A Rosin-Rammler (RR) distribution was used to describe the PSD for both fluidization and ball milling processes.