Abstract: Quantifying the heterogeneous gas-solid flow characteristics is of great significance to the design and optimization of this type of reactors. The formation and evolution of particle clusters result in the breakdown of the local equilibrium hypothesis, leading to the non-Maxwellian particle velocity distribution and the fail of classical kinetic theory of granular flow (KTGF). The particle movement characteristics and velocity distribution function in a fast fluidized bed were analyzed by using the experimental and data processing methods combing adaptive particle image velocimetry (PIV), particle tracking velocimetry (PTV) and digital image processing (DIA). It was found that the particle velocity distribution obviously deviated from the Maxwell distribution in both the gravity direction and the horizontal direction, showing a long-tailed off-peak or bimodal distribution. The bimodal distribution function can be used to fit the particle velocity distribution pretty well. In this work, the influence factors of anisotropy and non-Gaussian distribution characteristics of particle velocity distribution were further discussed. The particle velocity distribution function showed significant anisotropy in the horizontal and vertical directions. The deviation of particle velocity distribution function from the ideal distribution was positively correlated with the degree of particle clustering, the local particle velocity fluctuation and the particle concentration fluctuation, which may exhibit bimodal distributions in the near-wall regions. In order to analyze the relationship between particle velocity distribution function and mesoscale structure of fluidized bed more comprehensively, the energy-minimization multi-scale (EMMS) model was adopted to calculate the heterogeneous parameters. The consistency between the experimental results and the hypothesis of the dilute-dense phase coexistence showed the theoretical feasibility of the bimodal distribution.

Key words: particle image velocimetry, fluidized bed, solid velocity distribution, Heterogeneous structure, Mesoscale structure

摘要： 量化非均匀气固流动特征对流化床反应器的设计和优化具有重要意义。反应器内颗粒团聚物的形成和演化使得系统远离平衡状态，从而导致颗粒速度分布呈现非麦克斯韦分布特征。本工作利用自适应粒子图像测速(PIV)、粒子追踪测速技术(PTV)及数字图像处理(DIA)相结合的实验研究方法，对快速流化床中的颗粒运动特性和速度分布函数进行统计分析。研究发现，无论在沿重力方向还是水平方向，颗粒速度分布函数均明显偏离麦克斯韦分布，而呈现偏峰长拖尾或双峰分布特征。使用双峰分布函数可以较好地拟合不同实验条件下的颗粒速度分布。进一步探讨了颗粒速度分布函数的各向异性和非麦克斯韦分布的影响因素，发现颗粒速度分布函数偏离理想分布的程度与颗粒团聚程度、局域颗粒速度脉动量及颗粒浓度脉动量大小正相关。这说明颗粒团聚物的形成和演化使气固流化系统远离平衡态，从而导致颗粒速度分布呈现非麦克斯韦分布特征。最后结合能量最小多尺度(EMMS)模型对稀密相结构进行解析，并与实验获得的速度分布函数进行了对比，发现实验结果符合EMMS模型的稀密相共存假设，证明了采用双峰分布对颗粒速度分布函数进行近似在理论上可行。

关键词: 粒子图像测速, 流化床, 颗粒速度分布, 非均匀结构, 介尺度结构