Abstract
Many products incorporate into their design fibrous material with particular levels of permeability as a way to control the retention and flow of liquid. The production and experimental testing of these materials can be expensive and time consuming, particularly if it needs to be optimised to a desired level of absorbency. We consider a parametric virtual fiber model as a replacement for the real material to facilitate studying the relationship between structure and properties in a cheaper and more convenient manner. 3D image data sets of a sample fibrous material are obtained using X-ray microtomography and the individual fibers isolated. The segmented fibers are used to estimate the parameters of a 3D stochastic model for generating softcore virtual fiber structures. We use several spatial measures to show the consistency between the real and virtual structures, and demonstrate with lattice Boltzmann simulations that our virtual structure has good agreement with respect to the permeability of the physical material.
Highlights
Many products incorporate fibrous materials with carefully chosen permeability and absorption levels as a way to control liquid transport and retention in the product
X-ray microtomography is a common method for visualizing such fiber materials, providing high resolution 3D image data sets that capture the geometry of the fibers within the structure [4]
A stochastic model for generating 3D fiber structures was con structed and fitted to an X-ray microtomography image data set of a sample of fibrous material used for absorbent products
Summary
Many products incorporate fibrous materials with carefully chosen permeability and absorption levels as a way to control liquid transport and retention in the product. Analysis of the performance of such materials and the transport of fluid through the structure has been considered by a number of authors [1,2,3] Performing such analyses of the fiber structure requires the material to be well imaged and visualised. X-ray microtomography is a common method for visualizing such fiber materials, providing high resolution 3D image data sets that capture the geometry of the fibers within the structure [4]. This image data can be segmented to obtain a binary structure, which can be used to simulate fluid flow or other similar properties. This becomes more so if we wish to design a new material, requiring repeated production and imaging of different samples
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