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Numerical micro-scale modelling of the mechanical loading of woven la brics equipped with particles

机译：配备颗粒的织造La Brics机械负载的数值微级模型

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The equipping of polyester multifilament fabrics with functionalized micro particles for partial and targeted reduction of the size of continuous inter-yam pores in the fabric, utilizing the filtering effect of textile surfaces, has proven to be a very effective method for increasing the barrier properties of fabrics for use as surgical reusable textiles, cleanroom clothing or cleanable filter media. The objectives of this study were to understand the interrelationships of weaving parameters and fabric properties and to model the porous fabrics under loading conditions. Artificial Neural Networks were trained and tested in order to link the weaving and processing parameters with the fabric properties using the experimental data. Mean flow pore sizes and permeability values of woven fabrics under biaxial loading conditions were measured according to a method previously developed using a special sample holder connected to a conventional porosimetry. Finite element models of unit cells were developed and loaded virtually. Those models were transferred into voxel models and imported into software DNSlab, where they were virtually equipped with particles. For the simulation of the fluid flow, the Navier-Stokes equations wete solved numerically by the Lattice-Boltzmann method. The experimental and numerical studies show that pore size of barrier fabrics can be tailored using the developed methods and models. Important parameters are the fabric construction parameters and the particle size.
机译：利用纺织表面的滤波效果，用官能化的微颗粒配备官能化微颗粒的聚酯多丝织物的配合型微颗粒，已被证明是增加屏障性质的非常有效的方法用作手术可重复使用的纺织品，洁净室衣物或可清洁过滤介质的织物。本研究的目的是了解编织参数和织物性质的相互关系，并在装载条件下模拟多孔织物。培训并测试人工神经网络，以便使用实验数据将编织和处理参数与织物特性联系起来。根据先前使用连接到常规孔隙率测定法的特殊样品支架，根据先前开发的方法测量双轴负载条件下织物的平均流量孔径和渗透率值。开发和装载单位细胞的有限元模型。这些模型被转移到Voxel模型中并进口到软件DNSLAB中，在那里它们几乎配备了颗粒。为了模拟流体流动，Navier-Stokes方程由格子-Boltzmann方法数值求解。实验和数值研究表明，可以使用开发的方法和模型来定制屏障织物的孔径。重要的参数是织物施工参数和粒径。

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