Abstract

This paper proposes a novel multi-scale approach for the reliability analysis of composite structures that accounts for both microscopic and macroscopic uncertainties, such as constituent material properties and ply angle. The stochastic structural responses, which establish the relationship between structural responses and random variables, are achieved using a stochastic multi-scale finite element method, which integrates computational homogenisation with the stochastic finite element method. This is further combined with the first- and second-order reliability methods to create a unique reliability analysis framework. To assess this approach, the deterministic computational homogenisation method is combined with the Monte Carlo method as an alternative reliability method. Numerical examples are used to demonstrate the capability of the proposed method in measuring the safety of composite structures. The paper shows that it provides estimates very close to those from Monte Carlo method, but is significantly more efficient in terms of computational time. It is advocated that this new method can be a fundamental element in the development of stochastic multi-scale design methods for composite structures.

Highlights

  • Typical composite components are laminates comprising layers of fibre reinforced composite laminae, each of which are made of fibres embedded in matrix

  • It has a trend that perturbation based stochastic multi-scale finite element method (PSMFEM)-Second-Order Reliability Method (SORM) becomes close to multi-scale finite element method (MFEM)-Monte Carlo simulation (MCS) with the increase of the number of random variables, which introduces the nonlinearity of the limit-state functions (LSF)

  • As a by-product, PSMFEM-First-Order Reliability Method (FORM) provides sensitivity factors that measure the relative importance of each random variable

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Summary

Introduction

Typical composite components are laminates comprising layers of fibre reinforced composite laminae, each of which are made of fibres embedded in matrix. Sources of significant uncertainty include: variations in volume fractions of fibre and matrix, voids in the matrix and between fibres and matrix, imperfect bonding between constituents, cracks, fibre damage, random and/or contiguously packed fibres, misaligned fibres, temperature effects, non-uniform curing of the matrix material, residual stresses, etc. Uncertainties in these factors propagate to a larger scale and are reflected in variability of the stiffness and strength that characterise the overall structural behaviour [1,2,3,4,5,6,7].

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