Ke Zhenxia, Yu Lingjie, Wang Guanlin, Sun Runjun, Zhu Mengqiu, Dong Hanrui, Xu Yiqin, Ren Mengyue, Fu Sida, Zhi Chao
School of Textile Science and Engineering, Xi'an Polytechnic University, Xi'an 710048, China.
China-Australia Institute for Advanced Materials and Manufacturing, Jiaxing University, Jiaxing 314001, China.
Polymers (Basel). 2023 Jan 24;15(3):600. doi: 10.3390/polym15030600.
As a type of fiber system, nonwoven fabric is ideal for solid-liquid separation and air filtration. With the wide application of nonwoven filter materials, it is crucial to explore the complex relationship between its meso structure and filtration performance. In this paper, we proposed a novel method for constructing the real meso-structure of spun-bonded nonwoven fabric using computer image processing technology based on the idea of a "point-line-body". Furthermore, the finite element method was adopted to predict filtration efficiencies based on the built 3D model. To verify the effectiveness of the constructed meso-structure and simulation model, filtration experiments were carried out on the fabric samples under different pollution particle sizes and inlet velocities. The experimental results show that the trends observed in the simulation results are consistent with those of the experimental results, with a relative error smaller than 10% for any individual datum.
作为一种纤维系统,无纺布是固液分离和空气过滤的理想材料。随着无纺布过滤材料的广泛应用,探索其细观结构与过滤性能之间的复杂关系至关重要。本文基于“点-线-体”的思想,提出了一种利用计算机图像处理技术构建纺粘无纺布真实细观结构的新方法。此外,基于建立的三维模型,采用有限元方法预测过滤效率。为验证所构建的细观结构和模拟模型的有效性,对织物样品在不同污染粒径和入口速度下进行了过滤实验。实验结果表明,模拟结果观察到的趋势与实验结果一致,任何单个数据的相对误差均小于10%。