Reliability Analysis Of Composite Structures Research Articles

Multiscale reliability analysis of composite structures based on computer vision

The geometric uncertainties of composite structures are considered in the multiscale reliability problem. A convolutional neural network (CNN) is developed and trained using deep learning to link geometric uncertainties and the randomness of structural responses or performances. The CNN training set includes graphical samples and corresponding stress components and strength characteristics of the lamina. A method for generating a graphical sample is developed, which integrates the stochasticity of the fibre shape, misalignment, arrangement, volume fraction, matrix voids, and stacking sequences of the laminates. The corresponding stress components are simulated using the Kernal–Hashin model and laminate plate theory. A reliability analysis procedure is developed using a Monte Carlo simulation. Numerical cases are presented to demonstrate the validity of the proposed method.

Bayesian inference in validation of global MPP for the reliability analysis of composite structures

Realistic analysis of structure failures under uncertainties are due to be associated with the use of probabilistic methods. One of the main problems in structural reliability analysis of composite laminate structures is the possible existence of multiple MPP (Most Probable Failure Point). In this work, we propose a numerical inverse technique for the global MPP search as a function of the anisotropy of laminated composites. Therefore, the analysis considers the maximum loading capability of the composite structure for a prescribed reliability level. This is equivalent to solving a target reliability-based design optimization problem. A Bayesian method to estimate the probability of failure based on Monte Carlo simulation provides the validation of the results. The validation process demonstrates that the proposed methodology is adequate to estimate the probability of failure of the laminated composite structures. Furthermore, the paper outlines and discusses the sensitivity of reliability index under maximum loading variability for angle ply composites.

Stochastic multi-scale finite element based reliability analysis for laminated composite structures

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.

Multi-scale reliability analysis of composite structures – Application to the Laroin footbridge

This work aims at developing a new methodology for the reliability assessment of composite structures and their design optimization. It relies on the coupling of well established methods: homogenization scheme for the mechanical modelling of composite materials and reliability methods to account for their inherent variability. Moreover, such approach is based on an accurate treatment of inherent uncertainties of these mechanical systems at various scales, including microscopic and macroscopic levels, that provides new perspectives for structural design. As an illustration, we propose to apply the multi-scale reliability analysis on the case of the Laroin footbridge (France) with carbon–epoxy stay cables. Since the reliability assessment of such structure is evaluated through the fibre failure, numerical simulations require the coupling of reliability methods, finite element modelling to derive macroscopic loading within cables and micromechanics to estimate the effective elastic properties of composite and local responses within constituents. Results demonstrate the feasibility of the coupled approach at a structure scale and its main interests for the optimization phase of materials and engineering structures.