单分散非球形颗粒及球柱二元混合物流态化行为的测定

IF 4.5 2区 工程技术 Q2 ENGINEERING, CHEMICAL Advanced Powder Technology Pub Date : 2025-01-01 Epub Date: 2024-12-12 DOI:10.1016/j.apt.2024.104755
Yihao Wen , Haoshen Niu , Boyu Zhu , Jianjian Dai , Zihao Ma , Jia Yu , Xi Gao
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引用次数: 0

摘要

了解单分散非球形颗粒和含非球形颗粒的二元混合物的流化行为,对于更好地设计和优化流化床反应器具有重要意义。实验研究了颗粒形状对矩形鼓泡流化床中单分散颗粒和二元颗粒流化行为的影响。实验测量包括总压降、截面压降、混合和偏析。提出了一种机器学习辅助图像处理方法,从二元流化背景中分割不同颗粒,分析颗粒高度分布和非球形颗粒取向分布等动力学特性。实验结果表明,最小流化速度随球度的减小而减小,减小范围在0.63 ~ 1之间。非球形粒子的膨胀高度高于球形粒子。当取向角(轴向与水平方向夹角)为±75°时,圆柱形颗粒分散最多。随着柱状颗粒长径比的增大,球体和柱状混合物的Lacey混合指数减小,范围在1 ~ 5之间,对应于混合良好和混合不良的状态。实验结果可作为验证计算流体力学模型的基准数据。
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Measuring fluidization behaviors of monodisperse non-spherical particles and binary mixtures of spheres with cylinders
Understanding the fluidization behavior of monodisperse non-spherical particles and binary mixtures containing non-spherical particles is essential for better designing and optimizing fluidized bed reactors. This study experimentally investigated the effect of particle shapes on the fluidization behavior of monodispersed particles and binary particles in a rectangular bubbling fluidized bed. The experimental measurements include the total pressure drop, sectional pressure drops, mixing, and segregation. A machine learning-aided image processing method was developed to segment different particles from the background in binary fluidization and analyze particle dynamics, such as particle height distribution and non-spherical particle orientation distribution. The experimental results show that the minimum fluidization velocity decreases with a decrease in sphericity ranging from 0.63 to 1. Higher expansion height is observed for non-spherical particles than for spherical particles. Cylindrical particles disperse the most when the orientation angles (the angle between axial and horizontal directions) are ± 75°. The Lacey mixing index of sphere and cylinder mixtures decreases with the increase of the aspect ratio of cylindrical particles ranging from 1 to 5, corresponding to well and poor mixing states. The experimental results serve as benchmark data to validate computational fluid dynamics models.
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来源期刊
Advanced Powder Technology
Advanced Powder Technology 工程技术-工程:化工
CiteScore
9.50
自引率
7.70%
发文量
424
审稿时长
55 days
期刊介绍: The aim of Advanced Powder Technology is to meet the demand for an international journal that integrates all aspects of science and technology research on powder and particulate materials. The journal fulfills this purpose by publishing original research papers, rapid communications, reviews, and translated articles by prominent researchers worldwide. The editorial work of Advanced Powder Technology, which was founded as the International Journal of the Society of Powder Technology, Japan, is now shared by distinguished board members, who operate in a unique framework designed to respond to the increasing global demand for articles on not only powder and particles, but also on various materials produced from them. Advanced Powder Technology covers various areas, but a discussion of powder and particles is required in articles. Topics include: Production of powder and particulate materials in gases and liquids(nanoparticles, fine ceramics, pharmaceuticals, novel functional materials, etc.); Aerosol and colloidal processing; Powder and particle characterization; Dynamics and phenomena; Calculation and simulation (CFD, DEM, Monte Carlo method, population balance, etc.); Measurement and control of powder processes; Particle modification; Comminution; Powder handling and operations (storage, transport, granulation, separation, fluidization, etc.)
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