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.

中文翻译：

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使用行星式球磨机评估材料特性，使用混合人工神经网络-遗传算法方法模拟气固流化床中粒度分布的变化

摘要 本研究旨在使用行星式球磨作为材料性能的评估工具，其结果随后用于开发使用人工神经网络 (ANN) 的一系列材料在流化过程中粒度分布 (PSD) 变化的模型。 ） 方法。人们认为，诸如硬度、密度、脆性、结构等材料特性在颗粒磨损行为中起着至关重要的作用。不幸的是，考虑到存在的材料种类繁多，关于材料特性的信息很少。因此，行星球磨被提议作为一种快速评估技术来识别不同材料的特性。行星式球磨设备在大多数实验室都很容易获得，PSD 的减少类似于流化过程中的颗粒磨损过程。Rosin-Rammler (RR) 分布用于描述流化和球磨过程的 PSD。