Purpose

The purpose of this paper is to fundamentally develop a mathematical model for predicting the particle size distribution (PSD) in fluidized beds because their hydrodynamics depend on the PSD and its evolution during operation. To predict the gradual PSD change in a fluidized bed by using the population balance method (PBM), the kinetic parameter for agglomerate formation should be known and this parameter, in this work, is determined by the results of computational fluid dynamic–discrete element method (CFD-DEM) simulation.

Design/methodology/approach

Momentum and energy conservation equations and soft-sphere DEM are used to simulate the agglomeration phenomenon at high temperature in a two-dimensional air-polyethylene fluidized bed in bubbling regime. The Navier–Stokes equations for motion of gas are solved by the SIMPLE algorithm. Newton’s second law of motion is applied to describe the motion of individual particles. Collision between particles is detected by the no-binary search algorithm.

Findings

A correlation is proposed for estimating the kinetic parameter for agglomerate formation based on collision frequency, collision efficiency and inlet gas temperature. Based on the corrected kinetic parameter, the PBM is able to predict the PSD evolution in the fluidized bed in a fairly good agreement with the results of the CFD-DEM.

Research limitations/implications

The results of the agglomeration process cannot be compared quantitatively with experimental results. Because three-dimensional fluidized bed mostly contains millions of particles and simulating them takes a long computing time in DEM. As far as temperature is a dominant parameter in the agglomeration process, effects of inlet gas temperature are examined on the kinetic parameter. On the other hand, wider and deeper insights in which the effect of other parameters, such as velocity and so on will be studied, is one of the goals in the authors’ next works to compensate for the shortcomings in this work.

Originality/value

This study helps to understand the effect of the inlet gas temperature during the agglomeration process on the kinetic parameter and provides fundamental information in dealing with kinetic parameter to attain PSD in fluidized bed by the PBM.

中文翻译：

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结合CFD-DEM/PBM技术对流化床团聚现象的数值研究

目的

本文的目的是从根本上开发一个数学模型来预测流化床中的粒度分布 (PSD)，因为流化床的流体动力学取决于 PSD 及其在操作过程中的演变。为了使用群体平衡法 (PBM) 预测流化床中的 PSD 逐渐变化，应知道团聚体形成的动力学参数，并且在这项工作中，该参数由计算流体动力学 - 离散元方法的结果确定(CFD-DEM) 模拟。

设计/方法/方法

利用动量和能量守恒方程和软球DEM模拟了二维空气-聚乙烯流化床鼓泡状态下高温下的团聚现象。气体运动的 Navier-Stokes 方程通过 SIMPLE 算法求解。牛顿第二运动定律用于描述单个粒子的运动。粒子之间的碰撞由非二元搜索算法检测。

发现

提出了一种基于碰撞频率、碰撞效率和入口气体温度来估计团聚体形成动力学参数的相关性。基于校正后的动力学参数，PBM 能够预测流化床中的 PSD 演变，与 CFD-DEM 的结果非常吻合。

研究限制/影响

团聚过程的结果不能与实验结果进行定量比较。因为三维流化床大多包含数百万个粒子，在 DEM 中模拟它们需要很长时间的计算时间。就温度是团聚过程中的主要参数而言，研究了入口气体温度对动力学参数的影响。另一方面，将研究其他参数（如速度等）的影响的更广泛和更深入的见解是作者下一步工作的目标之一，以弥补这项工作的不足。

原创性/价值

该研究有助于了解团聚过程中入口气体温度对动力学参数的影响，并提供处理动力学参数以通过 PBM 获得流化床 PSD 的基本信息。