Random fiber networks are assemblies of elastic elements connected in random configurations. They are used as models for a broad range of fibrous materials including biopolymer gels and synthetic nonwovens. Although the mechanics of networks made from the same type of fibers has been studied extensively, the behavior of composite systems of fibers with different properties has received less attention. In this work we numerically and theoretically study random networks of beams and springs of different mechanical properties. We observe that the overall network stiffness decreases on average as the variability of fiber stiffness increases, at constant mean fiber stiffness. Numerical results and analytical arguments show that for small variabilities in fiber stiffness the amount of network softening scales linearly with the variance of the fiber stiffness distribution. This result holds for any beam structure and is expected to apply to a broad range of materials including cellular solids.

随机纤维网络是以随机配置连接的弹性元件的组件。它们被用作各种纤维材料的模型，包括生物聚合物凝胶和合成非织造布。尽管由相同类型的纤维制成的网络的力学已被广泛研究，但具有不同性能的纤维的复合系统的行为受到的关注较少。在这项工作中，我们从数值和理论上研究了不同机械性能的梁和弹簧的随机网络。我们观察到，在平均纤维刚度恒定的情况下，随着纤维刚度变异性的增加，整体网络刚度平均下降。数值结果和分析论证表明，对于纤维刚度的微小变化，网络软化量与纤维刚度分布的方差成线性比例。该结果适用于任何梁结构，并且预计适用于包括多孔固体在内的广泛材料。