Validation of pressure drop prediction and bed generation of fixed-beds with complex particle shapes using discrete element method and computational fluid dynamics
Validation of pressure drop prediction and bed generation of fixed-beds with complex particle shapes using discrete element method and computational fluid dynamics
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DOI：
10.1002/aic.16967
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发表时间：
2020-03-12
期刊：
影响因子：
3.7
通讯作者：
Kraume, Matthias
中科院分区：
文献类型：
--
作者：
Jurtz, Nico;Wehinger, Gregor D.;Kraume, Matthias
具有低管-颗粒直径比的催化固定床反应器在工业应用中被广泛使用。这种反应器类型中的非均匀填充形态导致显著影响反应器性能的局部流动现象。粒子分辨计算流体动力学已成为一种预测性的数值方法来分析的流量，温度，和物种场，以及局部反应速率空间，因此，可以被用作设计工具，以开发新的改进的催化剂形状。过去提出的大多数验证研究仅限于简单的颗粒形状。更复杂的催化剂形状被认为可以提高反应器的性能。填充各种工业相关的复杂颗粒形状的固定床反应器的模拟工作流程，并验证对实验数据的床层空隙率和压降。工业相关的加载策略进行了数值复制和颗粒取向和床层空隙率的影响进行了研究。
Catalytic fixed-bed reactors with a low tube-to-particle diameter ratio are widely used in industrial applications. The heterogeneous packing morphology in this reactor type causes local flow phenomena that significantly affect the reactor performance. Particle-resolved computational fluid dynamics has become a predictive numerical method to analyze the flow, temperature, and species field, as well as local reaction rates spatially and may, therefore, be used as a design tool to develop new improved catalyst shapes. Most validation studies which have been presented in the past were limited to simple particle shapes. More complex catalyst shapes are supposed to increase the reactor performance. A workflow for the simulation of fixed-bed reactors filled with various industrially relevant complex particle shapes is presented and validated against experimental data in terms of bed voidage and pressure drop. Industrially relevant loading strategies are numerically replicated and their impact on particle orientation and bed voidage is investigated.