Computational characterization of nonwoven fibrous media: I. Pore-network extraction and morphological analysis
Computational characterization of nonwoven fibrous media: I. Pore-network extraction and morphological analysis
复制标题
DOI：
10.1103/physrevmaterials.4.083803
复制
发表时间：
2020-08
影响因子：
3.4
通讯作者：
Fang Wang;U. Schiller
中科院分区：
文献类型：
--
作者：
Fang Wang;U. Schiller
非织造纤维材料是一类独特的多孔材料，广泛用于过滤和分离应用。纤维介质中复杂的孔结构，具有高连通性和低弯曲度，在提高过滤效率的同时防止过滤器结垢。孔径分布是通过调整纤维介质的微观结构来预测和改善传输特性的关键。然而，在实验中很难获得孔隙空间的统计性质，而且往往只报道了有效的几何性质，如水力半径和比表面积。在这项研究中，我们使用了一个计算框架，并生成了具有广泛孔隙率的逼真非织造纤维介质。通过提取分水岭分割的孔隙空间的子网络得到孔隙网络，并分析了孔喉大小及其连通性的统计分布。我们发现，纤维的随机取向对有效几何性质及其与孔隙率的依赖关系有显著的影响。我们研究了纤维尺寸、取向和纤维间重叠等工艺参数的影响，以此作为预测非织造纤维介质传输特性的前提。这种计算方法可以与实验成像技术相结合，从而能够根据特定制造工艺产生的统计孔隙空间属性快速表征多孔微结构。
Nonwoven fibrous materials are a unique class of porous materials that are widely used for filtration and separation applications. The complex pore structure in fibrous media, with high connectivity and low tortuosity, enhances filtration efficiency while preventing filter fouling. The pore size distribution is a key to predicting and improving transport properties by tailoring the microstructure of fibrous media. However, the statistical properties of the pore space are not easily accessible in experiments, and often only effective geometric properties such as hydraulic radius and specific surface area are reported. In this study, we employ a computational framework and generate realistic nonwoven fibrous media with a wide range of porosities. We obtain the pore network by extracting a subnetwork of the watershed segmentation of pore space and analyze the statistical distribution of pore and throat sizes and their connectivity. We find that a random fiber orientation has a pronounced effect on the effective geometric properties and their dependence on porosity. We investigate the influence of processing parameters such as fiber size, orientation, and overlaps between fibers as a prerequisite to predicting transport properties of nonwoven fibrous media. The computational approach can be combined with experimental imaging techniques, which enables rapid characterization of porous microstructures in terms of the statistical pore space properties resulting from specific manufacturing processes.