• Fabro, Adriano Todorovic
• Bickerton, S.
• Mace, Brian
• Battley, M.
• Gan, J. M.
• Ferguson, Neil

Abstract

Typically, there is variability in the properties of fibre-reinforced composites – material content, thickness, stiffness etc. – and this variability is often spatially correlated. Finite element (FE) or numerical models can predict the response of such panels, but the spatially correlated nature of the variability must be represented in the model. However, characterising the variability, and especially the spatial correlation, is problematical. In this study the data is first generated by an automated optical process: light transmissibility measurements are taken of a dry chopped strand mat. The intensity of the consequent image is post-processed to describe the fibre density as a random field using Karhunen-Loeve decomposition. Previous measurements have shown a strong correlation between the density of the mat and the tensile modulus, so the information is then used to infer the statistics of the stiffness matrix in the FE model. Subsequent realisations of the random field are then used, in a Monte Carlo simulation, to predict the statistics of the natural frequencies and frequency responses. The method provides an automated approach to the characterisation of spatial variability and hence the prediction of the statistics of the vibrational response.

Topics

• density
• impedance spectroscopy
• simulation
• composite
• random
• decomposition