Study on friction pressure drop characteristics of gas flow through multi-size irregular high-purity magnesia bed layer

As the primary production equipment for high-purity magnesia, shaft kilns are extensively employed in metallurgical and chemical processes. Understanding and optimizing the internal flow dynamics and heat transfer mechanisms within high-purity magnesia shaft kilns can significantly enhance production efficiency and product quality while reducing energy consumption and mitigating environmental impacts. Particularly, the airflow characteristics in shaft kilns directly impact burner selection, bed height, fan selection, and fan power consumption, consequently affecting heat transfer properties within the kilns. The airflow pressure drop across the high-purity magnesia particle bed under varying operational conditions was systematically investigated via experimentation utilizing a self-built experimental setup. Initially, the fundamental macroscopic attributes of high-purity magnesia particles, including particle size distribution, density, sphericity, and voidage, were meticulously quantified. Subsequently, employing the aforementioned experimental platform, the impacts of differing gas apparent flow velocities and particle equivalent diameters on gas flow pressure drop were assessed and analyzed. Incorporating considerations for the wall effect, the existing frictional pressure drop correlation was recalibrated through fitting procedures to derive an experimental correlation characterizing gas flow pressure drop within the high-purity magnesia particle bed layer, with subsequent verification of its applicability. The findings reveal a linear relationship between the wall-corrected frictional pressure drop, f w and the wall-corrected particle Reynolds number, Rew, with a gradual increase in the slope of the curve. Considering the substantial deviation between experimental data and previously established resistance correlation equations, a novel resistance correlation applicable to the high-purity magnesia bed was formulated through data fitting. The pressure drop correlation obtained in the present work can well predict the gas flow resistance in the multi-size high-purity magnesia bed with an error of less than 7 %.