The mechanical behaviors of random curved fiber networks by numerical simulations. (15th May 2023) - Li, Zhinan; Qian, Yixing; Bao, Qiang; Yang, Zhenyu; Lu, Zixing
Highlights: The theoretical method is presented for calculating the crosslinks density of curved fiber networks. The coupling effects of structural parameters on mechanical properties of RCFNs are revealed by numerical simulations. An energy ratio is defined to describe the transition from bending dominated to stretch dominated. The scaled yield strength of RCFNs has a nonlinear relationship with the curvature. Abstract: Random curved fiber networks (RCFNs) are ubiquitous in biological materials and artificial composites, attracting much attention because of their unique mechanical properties and functionalities. Based on numerical simulations, the effects of fiber morphology, fiber aspect ratio and relative density on mechanical properties of two dimensional (2D) RCFNs are investigated in terms of the elastic modulus, yield strength as well as energy ratio of stretching to bending deformation. Based on the conditional probability density function (CPDF), a general theoretical model is extended for calculating the crosslink density of fiber networks, which elucidates the independence of crosslink density on fiber shape in RCFNs. According to numerical results, the elastic modulus and yield strength decrease with rising fiber curvature and are enhanced by increasing of aspect ratio and relative density. The influence of fiber aspect ratio in RCFNs exhibits thresholds, beyond which the mechanical properties will reach upper limits for constant curvature. The scaled yield strength to modulus of RCFNs versus curvature is found to collapse into a nonlinear curve regardless of aspect ratios. The energy ratio is influenced by fiber curvature more vigorously which is explained by deformations of curved segments and load paths deviations. This paper is expected to contribute to deep understanding of relationships between overall mechanical properties and structural parameters of RCFNs.