Experimental analysis of particle clustering in moderately dense gas–solid flow
Experimental analysis of particle clustering in moderately dense gas–solid flow
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DOI：
10.1017/jfm.2021.1024
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发表时间：
2021-12
影响因子：
3.7
通讯作者：
Kee Onn Fong;F. Coletti
中科院分区：
文献类型：
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作者：
Kee Onn Fong;F. Coletti
摘要在碰撞气固两相流中，经常会观察到稠密的颗粒团簇，它们对混合物的输运性质有很大的影响。这种现象的表征和预测是具有挑战性的，由于有限的光学访问，所涉及的尺度范围广，不同机制的相互作用。在这里，我们考虑了一个实验室设置，其中颗粒落在方形垂直管道中向上移动的空气中：提升管反应器中的经典配置。使用非粘性的，单分散的，球形颗粒和独立地改变固体体积分数（$\varPhi _V = 0.1\，\% - 0.8\，\%$）和散装气流雷诺数（$Re_{bulk} = 300 - 1200$）的能力，使我们能够隔离的多相动力学的关键要素，提供了第一个实验室观察团簇诱导的湍流。高于阈值$\varPhi _V$，该系统表现出强烈的浓度和速度的波动，通过高速成像测量通过背光技术，返回光学深度平均场。时空自相关揭示了密集和持久的中尺度结构下降速度比周围的粒子和尾随长尾流。这些被显示为视觉观察到的集群的统计足迹，主要在墙壁附近发现。它们通过渗流分析来识别，在时间上进行跟踪，并在大小，形状，位置和速度方面进行表征。较大的星团密度更大，寿命更长，下降速度也更快。在目前的粒子斯托克斯数，阈值$\varPhi _V \sim 0.5$ %（很大程度上独立于$Re_{bulk}$）是一致的，当连续碰撞之间的典型间隔小于粒子的响应时间时，集群出现的看法。
Abstract In collisional gas–solid flows, dense particle clusters are often observed that greatly affect the transport properties of the mixture. The characterisation and prediction of this phenomenon are challenging due to limited optical access, the wide range of scales involved and the interplay of different mechanisms. Here, we consider a laboratory setup in which particles fall against upward-moving air in a square vertical duct: a classic configuration in riser reactors. The use of non-cohesive, monodispersed, spherical particles and the ability to independently vary the solid volume fraction ($\varPhi _V = 0.1\,\% - 0.8\,\%$) and the bulk airflow Reynolds number ($Re_{bulk} = 300 - 1200$) allows us to isolate key elements of the multiphase dynamics, providing the first laboratory observation of cluster-induced turbulence. Above a threshold $\varPhi _V$, the system exhibits intense fluctuations of concentration and velocity, as measured by high-speed imaging via a backlighting technique which returns optically depth-averaged fields. The space–time autocorrelations reveal dense and persistent mesoscale structures falling faster than the surrounding particles and trailing long wakes. These are shown to be the statistical footprints of visually observed clusters, mostly found in the vicinity of the walls. They are identified via a percolation analysis, tracked in time, and characterised in terms of size, shape, location and velocity. Larger clusters are denser, longer-lived and have greater descent velocity. At the present particle Stokes number, the threshold $\varPhi _V \sim 0.5$ % (largely independent from $Re_{bulk}$) is consistent with the view that clusters appear when the typical interval between successive collisions is shorter than the particle response time.