Different forms of close-packed yarns can be produced by varying the number of monofilaments in the core region, ranging from one to five. Numerous efforts have been made to model or simulate the mechanical response of close-packed yarns; however, previous studies have predominantly focused on one or two monofilaments in the core. In this study, we propose an analytical approach that combines a geometrical model with an artificial neural network (ANN) to predict the tensile behavior of close-packed yarns containing 2 to 5 monofilaments in the core region. The novelty of this hybrid model lies not only in accounting for more than two monofilaments in the core but also in extending the prediction range from elastic to viscoelastic-plastic behavior. Validation of the proposed method showed excellent agreement between experimental and theoretical results. Numerical simulations further confirmed that the results align with theoretical predictions, demonstrating the model’s accuracy in predicting the tensile behavior of close-packed yarns. This modeling approach has the potential to significantly improve the understanding and modeling of textile structures.
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