Novel method of air distributor design for enhancing bed stability and reducing impurities in gas–solid fluidized bed system

Estimation of Bed Expansion and Separation Density of Gas–Solid Separation Fluidized Beds Using a Micron-Sized-Particle-Dense Medium

Coal is the dominant energy resource in China. With the Chinese policy of committing to reducing peak carbon dioxide emissions and achieving carbon neutrality, coal separation has recently become a hot topic, especially the fluidized separation of fine particles. In this study, micron-sized particles were introduced to ameliorate the properties of the traditional fluidized bed. The expansion characteristics of the micron-sized-particle-dense medium were explored. A bed expansion prediction model of the micron-sized-particle-dense medium was established, and the prediction error was about 10%, providing a theoretical basis for understanding the distribution characteristics of the bed. This model also helped predict the bed density in the presence of a micron-sized-particle-dense medium, and the prediction accuracy was between 85% and 92%, providing a theoretical basis for selecting and popularizing fluidized beds for industrial separation.

Modelling of Hard Coal Beneficiation Process Utilising Negative Pressure Pneumatic Separator

The dry separation methods for coal beneficiation have been regaining attention in the past decades. A number of improved or newly designed devices have been developed—one of them is a negative pressure pneumatic separator (NPPS). The said method of separation is based on the differences in the physical properties between coal and gangue minerals, such as the grain density, size, and shape. The aim of the hereby presented work was to develop working models describing the operation of the NPPS. To validate the models, the calculation results were compared with experimental results of the tests carried out in the previous study on the topic. Based on the findings it can be inferred that the models accurately predict the separation results, i.e., the majority of results are within the range of estimated measurement uncertainties. Consequently, the models allow one to optimise the process to obtain the products with desirable properties.