Stochastic local load redistribution in the fibre bundle model of nanopillar arrays

Abstract

Abstract. We study the breakdown of the nanopillar arrays subjected to axial loading. The pillar-strength-thresholds are drawn from a given probability distribution. Pillars are located in the nodes of the supporting regular lattice. In this work we introduce stochastic local load sharing -after pillar breakdown each of its nearest intact neighbours obtains a random fraction of the failing load. Two types of loading procedure are employed, namely quasi-static and finite force. We analyse critical loads, catastrophic avalanches as well as probabilities of cascade and breakdown.

Analysis of damage processes in nanopillar arrays with hierarchical load transfer

“…is an increasing function of N [4,5]. One exception to the reported rule is the system with 4 = z and .…”

“…Under external load, materials undergo a damage process that leads to complete failure if the load increase is not stopped. In this work we study breakdown processes in axially loaded metallic nanopillar arrays [4,5]. The arrays of nanopillars are encountered in many areas of nanotechnology and reveal the potential applicability as components for the fabrication of electro-mechanical sense devices.…”

True Strength of Ceramic Fiber Bundles: Experiments and Simulations

“…Enhancing previous simulations [ 15 ], a self-growing hexagonal fiber placement setup was developed to represent the circular cross-section arrangement within a bundle. This approach was based on the triangular lattice geometry of Derda [ 24 ]. This option avoided some problems related to the by square matrix approach and allowed the simulation to be executed for almost any nominal count of virtual fibers [ 4 , 15 ].…”

Statistical analysis of mechanical damage in nanopillar arrays with mixed-mode load transfer

“…From 5 . 0 = g , the results for hexagonal lattice start to visibly differ from the results obtained for square and triangular geometries, while the results for these two geometries are almost equal up to In our previous works, we have noticed that for the LLS model the distribution of c σ can be fitted by three-parameter skew normal distribution (SND) with probability density function [9,10]:…”