Sentence examples for predict the fabric from inspiring English sources
In the present research, the artificial neural network (ANN) has been applied to predict the fabric apparent parameters.
Fabric structure plays a critical role for predicting the fabric properties.
This shell element takes advantage of a simple physics-based analytical relationship to predict the behaviour of the fabric's warp and weft yarns under general applied displacements in these directions.
We generate a physically motivated continuum model that can both simulate existing fabrics and predict the behavior of novel fabrics based on the properties of the yarns and the weave.
Analytical equations are provided to predict both the fabric locking and wrinkling onsets under these characterization tests, and verified experimentally on a carbon fiber plain woven fabric.
The approach was incrementally employed whereby the model predicts the composite fabric unit cell effective modulus, processing-induced strains and stresses (thermal expansion and chemical shrinkage) during cure.
In this research, finite element (FE) models were built up and used to predict the response of woven fabrics with different structural parameters, including fabric structure, thread density of the fabric and yarn linear density.
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.
A new computational approach is developed to predict the impact behaviour of fabric panels based on the detailed response of the smallest repeating unit (unit cell) in the fabric.
This article presents a numerical framework to predict the mechanical behavior of knitted fabrics from their discrete structure at the fabric yarn level, i.e., the mesostructure, utilizing the hierarchical multiscale method.
The first model uses the direct-step finite element method to predict the ballistic properties of fabric armour while the second model is analytical.
