Modeling

While there are several 2-D and 3-D analytical models developed for predicting the permeability of fibrous disordered media, there are not many numerical works that compare the predictions of these models with that of real media. In this work, we present a series of numerical simulations performed on the microstructure of a real fibrous media. An efficient procedure is presented for reconstructing 3-D images from the 2-D images of the real fibrous media and processing them for the purpose of performing fluid flow simulation. Digital Volumetric Imaging (DVI) of a typical hydroentangled fibrous fabric is obtained, as an example, and its permeability is computed. These results are compared with those obtained from the analytical equations given in the literature.

The coat-hanger die has been widely used in spun-melt nonwoven production line both in China and all over the world. Nevertheless, too many generalizations have been made in theoretically optimizing the design for different polymers. Based on the theories of fully developed flowing models with non-Newtonian fluid flowing in a circular conduit and in the slot, this paper develops the design theories of the coat-hanger shaped die fluid channel, to realize uniformly distributed flux, equivalent pressure drop and equal retention time at the die exit across the die breadth. Actual designs are built from the theoretical models and the flow patterns are compared to the theoretical predictions. Furthermore, the forces acting on the melt channel and die are predicted and confirmed. Results show that the quality of the nonwoven fabrics produced from both the spunbond and melt blown lines configured with the optimized coat hanger and die are notably improved.

Conductive fibrous structures have already been extensively studied [1]. However, those were not textile materials but electrodes for batteries. Conductive nonwoven have been used, for example, as heating elements in car seats.
In order to compute the equivalent electrical resistance of a web, we first simulate the nonwoven structure using the simulation described in [2]. The web structure is then transformed into a non oriented weighted graph where the nodes are the contact points between the fibers. Assuming all the fibers have the same diameter, the weights of the edges can be considered to be the fiber lengths between those contacts instead of the resistances. The graph is then reduced using generalized Kirshoff transformations until the equivalent length is obtained. The process is illustrated in Figures 1 to 3.

 

Figure 1: simulated web

Figure 2: Graph generated from the web

Figure 3: Graph undergoing reduction

Statistical Process Models are used to identify the influence of production line parameters on the resulting properties of the produced fleece. The models described in this presentation are based on data acquired in mechanical tests of the product as well as with the use of an online scanning system for the fibre orientation.

Analysis algorithms allow to identify the relationship between the mechanical properties in machine direction and cross direction (MD:CD-ratio) on the basis of the visual analytical data

From the derived orientation distribution the MD:CD ratio of the stiffness of the fleece can be calculate. Models were developed using linear and non-linear regression approaches. The results project both the effects of selected production line parameters on the orientation distribution and the resulting mechanical characteristics. The linear regression was implemented using second order parameter terms. Neuronal networks were used for the non-linear analysis.

The application of an online orientation measurement system can be used for the adaptation of a process control at an early stage.

Hydroentanglement is arguably the fastest growing bonding method in the nonwoven industry. Hydroentangling uses fine, closely spaced, high-speed water jets to strike the web on a drum or a belt and form a fabric by rearranging and entangling the fibers in the web. It  also offers the ability to split bicomponent fibers and therefore, when used as the method of bonding for splittable fibers, the structure is split and bonded in one step.  However, there is little information available in the open literature dealing with the manner in which fibers split and bond and the materials-process-performance interactions.  Currently, only the overall degree of the fiber splitting can only be determined indirectly by measuring air permeability, thickness, density or mechanical properties.  These however, offer little insight with respect to the degree of splitting and/or the local variations in splitting through the thickness of the material. 

We explored three dimensional structural analyses to fully understand and characterize splitting in hydroentangled multi-component fabrics utilizing Digital Volumetric Imaging (DVI). It was found that lower fabric density as measured by solid volume fraction, higher degree of splitting and a higher thickness direction fiber orientation was evident at the jet streak valley position. Splitting was found to be more dominant on the surface of the fabrics. Washing the fabric increased fiber splitting and also resulted in more uniform splitting, but did not result in any significant change in local fiber orientation, i.e., the structure.

Permeability is one of the most important characteristics of a fibrous filter. While numerous analytical, numerical, and experimental published works are available for predicting the permeability of the filters made up of fibers with a unimodal fiber diameter distribution, there are not many studies dedicated to bicomponent (bimodal) fibrous media. In this work, permeability of bicomponent fibrous filters is calculated by solving the air flow governing equations in a series of virtual geometries generated using GeoDict CFD code that resemble the microstructure of a fibrous medium. These simulations are deployed to find a monocomponent equivalent diameter for each bicomponent filter medium that could be used in the existing expressions of monocomponent media for permeability prediction.