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Time-dependent statistical failure of fiber networks
Amanda Mattsson1, Tetsu Uesaka1
1Department of Chemical Engineering, Mid Sweden University, Sundsvall, Sweden 85170.
Abstract:
Numerical simulations of time-dependent stochastic failure of fiber network have been performed by using a central-force, triangular lattice model. This two-dimensional (2D) network can be seen as the next level of structural hierarchy to fiber bundles, which have been investigated for many years both theoretically and numerically. Unlike fiber bundle models, the load sharing of the fiber network is determined by the network mechanics rather than a preassigned rule, and its failure is defined as the point of avalanche rather than the total fiber failure. We have assumed that the fiber in the network follows Coleman's probabilistic failure law [B. D. Coleman, J. Appl. Phys. 29, 968 (1958)] with the Weibull shape parameter β=1 (memory less fiber). Our interests are how the fiber-level probabilistic failure law is transformed into the one for the network and how the failure characteristics and disorders on the fiber level influence the network failure response. The simulation results showed that, with increasing the size of the network (N), weakest-link scaling (WLS) appeared and each lifetime distribution at a given size approximately followed Weibull distribution. However, the scaling behavior of the mean and the Weibull shape parameter clearly deviate from what we can predict from the WLS of Weibull distribution. We have found that a characteristic distribution function has, in fact, a double exponential form, not Weibull form. Accordingly, for the 2D network system, Coleman's probabilistic failure law holds but only approximately. Comparing the fiber and network failure properties, we found that the network structure induces an increase of the load sensitivity factor ρ (more brittle than fiber) and Weibull shape parameter β (less uncertainty of lifetime). Superimposed disorders on the fiber level reduce all these properties for the network.
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