Thin fiber networks are widely represented in nature and can be found in man-made materials such as paper and packaging. The strength of such materials is an intricate subject due to inherited randomness and size-dependencies. Direct fiber-level numerical simulations can provide insights into the role of the constitutive components of such networks, their morphology, and arrangements on the strength of the products made of them. However, direct mechanical simulation of randomly generated large and thin fiber networks is characterized by overwhelming computational costs. Herein, a stochastic constitutive model for predicting the random mechanical response of isotropic thin fiber networks of arbitrary size is presented. The model is based on stochastic volume elements (SVEs) with SVE size-specific deterministic and stochastic constitutive law parameters. The randomness in the network is described by the spatial fields of the uniaxial strain and strength to failure, formulated using multivariate kernel functions and approximate univariate probability density functions. The proposed stochastic continuum approach shows good agreement when compared to direct numerical simulation with respect to mechanical response. Furthermore, strain localization patterns matched the one observed in direct simulations, which suggests an accurate prediction of the failure location. This work demonstrates that the proposed stochastic constitutive model can be used to predict the response of random isotropic fiber networks of arbitrary size.
翻译:素纤维网络在性质上具有广泛的代表性,在纸质和包装等人造材料中可以找到。这种材料的强度是一个复杂的问题,其原因是遗传的随机性和大小依赖性。直接纤维级数字模拟可以使人们深入了解这类网络组成组成部分的作用、其形态和对产品强度的安排。然而,随机生成的大型和稀薄纤维网络的直接机械模拟具有压倒性的计算成本的特征。在这里,提出了预测任意大小的异质薄纤维网络随机机械反应的随机机械化结构模型。模型基于SVE具体大小确定性和随机结构法参数的随机体积元素(SVES)。网络的随机性由非氧化性紧张和衰竭强度的空间领域描述,使用多变内核功能和粗微异性概率密度功能来制定。拟议的随机连续分析方法显示,与直接数字模拟机械反应相比,具有良好的一致性。此外,对结构型号网络的任意性数量要素进行模型的模拟表明,所观测到的构造性模型的准确性反应是精确性。