Journal of Inorganic Materials

   

Numerical Simulation of Particle Classification for Spent Hydrogenation Catalyst

ZHAO Lijuan1,2, TAN Zhe1,2, ZHANG Xiaoguang1,2, JIANG Guosai1,2, TAO Ran1,2, PAN Dean2,3,4   

  1. 1. Institute of Circular Economy, Beijing University of Technology, Beijing 100124, China;
    2. College of Materials Science and Engineering, Beijing University of Technology, Beijing 100124, China;
    3. State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China;
    4. College of Resources and Safety Engineering, Chongqing University, Chongqing 400044, China
  • Received:2025-01-18 Revised:2025-01-18
  • Contact: ZHANG Xiaoguang, professor. E-mail: zhangxg@bjut.edu.cn; PAN Dean, professor, E-mail: pandean@bjut.edu.cn
  • About author:ZHAO Lijuan (1997–), female, PhD candidate. E-mail: zhaolijuan97@163.com
  • Supported by:
    Major Research and Development Program in Yichun City (40009016202301)

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

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