Simulation of Draping Behavior of Woven Fabrics with an Optimized Yarn-Level Numerical Model 


Vol. 24,  No. 7, pp. 2503-2519, Jul.  2023
10.1007/s12221-023-00240-6


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  Abstract

Simulation of fabric draping behavior (DB) is very important for the optimization of the process of producing different types of fabrics and the upgrading of clothing design software programs. The DB of fabrics is greatly influenced by their materials and the interaction of their warp and weft yarns (WAWY). In this study, an optimized yarn-level model is used to simulate a woven fabric. The model simulates the tensile, flexural and torsional behavior of WAWY separately and deals with their interactions as well. The weave pattern and the density of 18 samples of woven fabrics, their tensile, flexural and torsional properties, and the count of their WAWY are analyzed to simulate the DB of the samples. Then, to reduce the error between the real and the simulated fabric, the coefficients of the tensile, flexural and torsional forces of the WAWY are optimized using the Imperialistic Competitive Algorithm (ICA). To evaluate the efficiency of the model, the DB of the fabric samples is also simulated using the mass-spring method and the results are compared. As it is found, the results of fabric drape simulation based on the type and the texture density at the yarn level are near to the real fabric behavior compare to previous methods. It is also shown that the optimized yarn-level model is able to simulate the DB of woven fabrics only with an error of 5.4%. Furthermore, the proposed model reduces the simulation error averagely for 4.8%, as compared to non-optimized yarn-level models.

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  Cite this article

[IEEE Style]

M. Kargar, P. Payvandy, V. Mozafary, "Simulation of Draping Behavior of Woven Fabrics with an Optimized Yarn-Level Numerical Model," Fibers and Polymers, vol. 24, no. 7, pp. 2503-2519, 2023. DOI: 10.1007/s12221-023-00240-6.

[ACM Style]

M. Kargar, P. Payvandy, and V. Mozafary. 2023. Simulation of Draping Behavior of Woven Fabrics with an Optimized Yarn-Level Numerical Model. Fibers and Polymers, 24, 7, (2023), 2503-2519. DOI: 10.1007/s12221-023-00240-6.

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