Abstract
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.
Original language | English (US) |
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Article number | 538 |
Journal | Materials |
Volume | 12 |
Issue number | 3 |
DOIs | |
State | Published - Feb 11 2019 |
Funding
Funding: The authors at the Royal Institute of Technology acknowledge and thank the VINN Excellence center BiMaC Innovation and its industrial partners as well as ÅForsk and The Swedish Research Council, grant number 2015-05282, for their financial support of this research. The computations resources were provided by the Swedish National Infrastructure for Computing (SNIC) at HPC2N, Umeå (Project SNIC2017-1-175). Wei Chen is supported by Center for Hierarchical Design (ChiMad NIST 70NANB14H012).
Keywords
- Mechanical failure
- Multi-scale modeling
- Plastic softening
- Stochastic volume element (SVE)
- Strain localization
- Thin fiber networks
ASJC Scopus subject areas
- Condensed Matter Physics
- General Materials Science