Effect of spatially varying material properties on the post-buckling behaviour of composite panels utilising geodesic stochastic fields

The post-buckling behaviour of panels can be very sensitive to imperfections or variations in materials or geometry. This paper presents an ecient numerical model to calculate the eects of material stiffness variations on the non-linear response of a structure. This is done by first defining a geodesic mesh on which a unit variance random field is generated. This field uses the true geodesic distance on the structure to calculate how points in the field should be correlated. The fields generated are projected onto a 3D structural mesh which is used for assembly and post-processing of the structural model. The structural model, based on the Unified Formulation is capable of accurate non-linear calculations of both straight and curved elements. Baseline results generated using the implementation are compared to those in literature, and verified using Abaqus. Random material variations are then applied to the structure in a Monte Carlo analysis. The analyses show that the local variation of stiffness can have a variety of effects on the non-linear response of structures. Aside from the change of mean stiffness causing a change in bifurcation or limit point load, the different stiffness distributions can affect and trigger competing buckling modes and post-buckling modes and affect their corresponding post-buckling load-deflection paths

Improving the Static Structural Performance of Panels with Spatially Varying Material Properties Using Correlations

This chapter introduces an approach to systematically analyze stochastic distributions of spatially varying material properties in structures. The approach gives insight into how spatial variations of material properties affect the mechanical response of a structure. If sufficient knowledge of the production processes is available, this allows designers to analyze the probability that a certain design criterion (e.g. a certain buckling load level) is met. Stochastic structural analyses can be used to analyze how variations are correlated to a structural measure. This gives information on the sensitivity of the structure with respect to variations. In the present work, this is used to improve the structural performance by distributing a material pattern according to a pattern based on the sensitivity topology. This approach is illustrated by redistributing the material properties of an axially loaded panel on the basis of the correlation of the spatially varying Young’s modulus with the linear buckling load of the panel