A novel and efficient generalized anisotropic multiscale model for jersey knit fabrics
Source abstract
Abstract
Analysis of fabric deformation finds use in several engineering fields, including performance garments, biomedicine, and composite forming. In this work, we present a computational framework of analyzing the deformation of a jersey knit fabric under external loads using a novel multiscale model. The finite element model presented here does not assume orthotropicity and consists of a multiscale model, with the mesoscale comprising of an infinitely spanning truss structure representing loops of the knit fabric, and the macroscale comprising of shell elements. The tangent modulus of the shell elements at every iteration of the nonlinear solver was derived by simulating small principal deformations on the mesoscale truss structure. In turn the truss structure at every step was dictated by the deformation of the macroscale elements it is embedded within. The mechanical characteristics of the fabric depend on the properties of the truss structure elements, which were estimated through tensile tests. The model was compared to several test conditions and generally good agreement was found, with root mean square error between the simulations and tests ranging from 6.12% in the best fit to 21.81% in the poorest fit. This model is expected to yield accuracy similar to that in other multiscale models, over wider test conditions, and due to simplicity of the mesoscale elements, requiring less computational resources compared to multiscale, microscale and mesoscale models. Future work will aim to improve model accuracy by increasing definition in the truss constitutive equations.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Textile materials and evaluations · Structural Analysis and Optimization · Dyeing and Modifying Textile Fibers
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Massachusetts Institute of Technology
Funding
MathWorks
References (32)
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