Size Effects in Random Fiber Networks Controlled by the Use of Generalized Boundary Conditions.

Size Effects in Random Fiber Networks Controlled by the Use of Generalized Boundary Conditions.
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通过使用广义边界条件控制的随机光纤网络中的尺寸效应。

DOI:
10.1016/j.ijsolstr.2020.09.033
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发表时间:
2020-12-01
影响因子:
3.6
通讯作者:
Picu RC
Picu RC
中科院分区:
工程技术2区
文献类型:
--
作者:
Merson J;Picu RC

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以随机纤维网络作为主要结构成分的材料在工程和生物学中广泛遇到。这些材料的特点是多尺度的异质性,因此,它们的性能评估数值或实验通常取决于所考虑的样品的大小。在这项工作中,我们评估了尺寸对三维随机纤维网络的线性和非线性力学响应的影响,并确定其对材料参数和网络变形亲和力程度的依赖性。尺寸效应在非仿射网络中比在仿射网络中更明显,并且随着模型尺寸的增加而缓慢减小。为了消除这种影响,模型大于可以有效地解决与当前的计算机必须考虑。为了解决这个问题,我们提出了一种方法,允许使用相对较小的模型,同时准确地预测网络的小应变和大应变行为。该方法是基于广义边界条件介绍(,计算材料科学79,408-416),这是适应纤维材料的要求。
Materials with a stochastic fiber network as the main structural constituent are broadly encountered in engineering and in biology. These materials are characterized by multiscale heterogeneity and hence their properties evaluated numerically or experimentally are generally dependent on the size of the sample considered. In this work we evaluate the size effect on the linear and non-linear mechanical response of three-dimensional stochastic fiber networks and determine its dependence on material parameters and on the degree of affinity of network deformation. The size effect is more pronounced in non-affine than in affine networks and decreases slowly when the model size increases. In order to eliminate this effect, models lager than can be effectively solved with current computers have to be considered. To address this issue, we propose a method that allows using relatively small models, while accurately predicting the small and large strain behaviors of the network. The method is based on the generalized boundary conditions introduced in (, Computational Materials Science 79, 408–416), which are being adapted here to the requirements imposed by fibrous materials.
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影响因子: --
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