Relationship between bed heterogeneity, chord length distribution, and longitudinal dispersion in particulate beds.

Relationship between bed heterogeneity, chord length distribution, and longitudinal dispersion in particulate beds.
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颗粒床层非均质性、弦长分布和纵向分散之间的关系

DOI:
10.1016/j.chroma.2019.04.044
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发表时间:
2019
期刊:
Journal of chromatography. A
影响因子:
--
通讯作者:
U. Tallarek
U. Tallarek
中科院分区:
--
文献类型:
--
作者:
A. Svidrytski;D. Hlushkou;U. Tallarek

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我们分析了随机填充床体微结构之间的关系,我们通过颗粒间空隙空间的弦长分布分析将其量化,并用Pe= 10处的纵向弥散系数来表示相关的流动非均质性。随机收集的物理重建的填料与一组系统的计算机生成的单一尺寸球体填料相辅相成,对于这些填料,填充生成算法已经被仔细地调整,以实现床层孔隙度和微观结构非均质性的单调变化。这些计算机生成的填料和物理重建的填料在形态上最相关的区别是实际填料中存在的结构缺陷,如颗粒低聚物和较大的空隙以及污染物和颗粒碎片。这些缺陷影响了孔隙的形态,并引入了额外的结构非均质性。采用格子-Boltzmann方法模拟流体流动,采用随机游走粒子跟踪技术记录被动点状示踪剂在流场中的传输,得到了所有填料的流体动力弥散系数。我们提出了一个形态描述符σ/μ,它基于CLD(标准偏差σ和平均弦长μ)的统计参数,可以用来预测填充床中的分散系数,而与基本的粒度分布、填充生成协议、床层孔隙度和结构缺陷的发生无关。
We analyse a relationship between the bulk microstructure of randomly packed beds, which we quantify through chord length distribution (CLD) analysis of the interparticle void space, and the associated flow heterogeneity, as expressed by the longitudinal dispersion coefficient at a Péclet number ofPe= 10. A random collection of physically reconstructed packings is complemented with a systematic set of computer-generated packings of monosized spheres, for which the packing-generation algorithm has been carefully adjusted to realize a monotonic variation of the bed porosity and microstructural heterogeneity. The most relevant difference in the morphology between these computer-generated and the physically reconstructed packings are structural defects present in the real packings, such as particle oligomers and larger voids as well as contaminations and particle debris. These defects influence the pore space morphology and introduce additional structural heterogeneity. Hydrodynamic dispersion coefficients for all packings are derived by implementing the lattice-Boltzmann method to simulate fluid flow and a random-walk particle tracking technique to record the transport of passive, point-like tracers in the flow fields. We propose a morphological descriptor, σ/μ, based on statistical parameters of a CLD (standard deviation σ and mean chord length μ) that can be used to predict the dispersion coefficient in packed beds, independent from the underlying particle size distribution, packing-generation protocol, bed porosity, and the occurrence of structural defects.
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