废加氢催化剂颗粒分级数值模拟研究

doi:10.15541/jim20250027

摘要/Abstract

摘要： 废加氢催化剂具有报废量大、颗粒完整度高等特性,是再生催化剂载体的重要来源。现有废加氢催化剂回收技术大多关注其中的有价金属,对于载体颗粒的回收研究较少。本研究针对条状废加氢催化剂颗粒难以通过传统筛分实现有效分级的关键问题,创新性地提出采用流化床进行颗粒分级。采用计算流体动力学（CFD）和离散单元模型（DEM）耦合模拟的研究方法,结合响应面法（RSM）系统揭示了流化床分级的内在机理及工艺优化规律。研究表明,流化床通过气固两相流态化作用可实现不同长径比颗粒的高效分级,气体速度对分级效率的影响最为显著,其次是进料流量,进料口高度的影响相对较小。在一定的气体速度和进料口高度下,存在进料流量阈值,超过此值分级效率将会下降。通过建立Box-Behnken设计（BBD）模型,确定当气体速度为10.45 m/s,进料流量为7.50 t/h,进料口高度为3.50 m时,分级效率达到100%。本研究阐明了流化床分级过程的多物理场耦合机制,为废加氢催化剂回收过程中的载体颗粒预分级工艺提供了理论参考。

关键词: 废加氢催化剂, 回收, 分级, 数值模拟

Abstract: Spent hydrogenation catalysts are an important source of regeneration catalysts due to their large waste volume and high particle integrity. Most of the existing recovery technologies focus on recovering valuable metals, limited studies on the recovery of carrier particles. This study addresses the key challenge of ineffective classification of rod-shaped spent catalyst particles via traditional sieving due to their length-to-diameter ratios exceeding standard specifications. A fluidized bed classification process is innovatively proposed, and a coupled computational fluid dynamics (CFD) and discrete element method (DEM) simulation combined with response surface methodology (RSM) is employed to systematically elucidate the intrinsic mechanisms and optimization principles of fluidized bed classification. The results demonstrate that a fluidized bed enables efficient classification of particles with varying aspect ratios via gas-solid fluidization. Gas velocity is identified as the dominant factor influencing classification efficiency, followed by feed flow, whereas inlet height exhibits a negligible impact. A critical feed flow threshold exists under specific gas velocity and inlet height; exceeding this threshold leads to a decline in classification efficiency. By establishing a Box-Behnken design (BBD) model, optimal conditions are identified as a gas velocity of 10.45 m/s, feed flow of 7.50 t/h, and inlet height of 3.50 m, achieving 100% classification efficiency. This study clarifies the multi-physics coupling mechanism in fluidized bed classification and provides theoretical guidance for pre-classification processes of carrier particles during spent hydrogenation catalyst recycling.

Key words: spent hydrogenation catalyst, recovery, classification, numerical simulation

中图分类号:

X742

赵丽娟, 谭哲, 张晓光, 蒋国赛, 陶然, 潘德安. 废加氢催化剂颗粒分级数值模拟研究[J]. 无机材料学报, DOI: 10.15541/jim20250027.

ZHAO Lijuan, TAN Zhe, ZHANG Xiaoguang, JIANG Guosai, TAO Ran, PAN Dean. Numerical Simulation of Particle Classification for Spent Hydrogenation Catalyst[J]. Journal of Inorganic Materials, DOI: 10.15541/jim20250027.

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