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The degree of yarn waviness present in a 3D woven fabric can be affected by a range of factors including weave parameters and manufacturing-induced distortions such as fabric compaction.
The possibility of determining the yarn interlacing and weave parameters to obtain the desired realistic appearance and properties of fabric is still an open challenge in modern textile research.
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Mercerized and bleached 100% cotton woven fabric (the fabric parameters are plain weave, 138,84 g/m2, 56 ends/cm, 31 picks/cm, 50/1 yarn count) was used as substrate for the LBL process.
The feed-forward back-propagation ANN can predict the thermal insulation of the fabrics based on fabric construction parameters like weave, yarn count, thread density, weight and thickness as input.
Within a class of matrices (gauzes of given weave) a single numerical parameter suffices to distinguish between flow passage geometries and, therefore, serves for the acquisition of experimental flow data and its use in support of gas path design.
This experimental study shows the influence of specific parameters of cloths (like weave) on their dynamic behavior.
In a fabric system under ballistic impact, parameters like fiber characteristics, weave pattern and its type, number of fabric layers, surface density, missile parameters and impact parameters affect system energy absorption (Cunniff 1992).
A Multi-scale modeling approach is developed to predict the mechanical behaviors of the 3D woven composite fender with various design parameters from material and structure.
The network is used to predict the thermal insulation of woven textile fabrics based on these parameters before they are manufactured.
Histomorphometric parameters revealed statistically improved woven bone at the implant surface.
Several researchers have attempted to study the effect of fibre and yarn parameters on comfort characteristics of woven and knitted fabrics.
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