Sub-mesoscale modeling framework for woven fabrics using VAM-based geometrically-exact beam model
Abstract
In this work, a novel sub-mesoscale model of woven fabrics is developed using nonlinear finite
element methods. The main aim of the work is to develop a framework for modeling woven
fabrics. The yarns are modeled as beam elements that move freely in space and undergo large
deformations and rotations. A geometrically-exact beam theory (GEBT) used to model
composite beams of arbitrary cross sections is considered to model the yarns. The variational
asymptotic method (VAM), in tandem with the beam model, offers the advantage of modeling
beams of arbitrary cross sections. A surface-to-surface contact model is developed, considering
that the contact occurs at a point on the surface. The robustness of the contact model is
tested by designing a patch test. The overall mesoscale model of woven fabric is validated
using experimental results of biaxial tests performed on a plain glass weave woven fabric. The
biaxial simulation is performed by varying the number of yarns in the mesoscale model to
study the behavior of the model and demonstrate a representative volume element (RVE).
The yarns are made up of fbers twisted together. An isotropic model is an approximation
that works well on the mesoscale, but a more general model is needed to include fber-level
information. The yarns can be made of 10,000 to 60,000 fbers twisted together. Modeling
individual fbers and the interaction between them can be computationally expensive. The
variational asymptotic method-based homogenization (VAH) is used to get the homogenized
properties of yarn. A representative volume element of woven fabric, with yarns made of
coated fbers, is simulated by using homogenized properties obtained through VAH.
The framework can be extended by introducing friction between yarns in the contact.
Further, the uncertainty in the input parameters can be quantifed by propagating the
uncertainty through the system using uncertainty quantifcation (UQ) techniques.