Prediction of Residual Strains Due to In-Plane Fibre Waviness in Defective Carbon-Fibre Reinforced Polymers Using Ultrasound Data
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Abstract
Abstract Residual strains affect the properties and performance of composite components, therefore measuring and predicting them are important. The prediction of residual strains from a model can be achieved by two steps: the generation of a geometric ply map and the modelling based on that to predict 3D residual strains. A novel method for identifying the most effective algorithm for characterising fibre orientation for the geometric ply map using ultrasound C-scan data has been developed. Finite element models were generated based on the fibre-orientation data from three different algorithms: the Radon transform, 2D fast Fourier transform, and Sobel filter. The models were used to predict residual strains due to three different severities of in-plane fibre waviness induced in a set of 18 specimens. Stratified leave-one-out cross validation was applied to obtain optimum parameters for the three characterisation algorithms and to update the values of the coefficient of thermal expansion for the material. Residual strains on the surface of the specimens were obtained from calculations based on the out-of-plane displacements measured using a digital image correlation system. The predicted and measured residual strain maps were decomposed into feature vectors using orthogonal polynomials to reduce data dimensionality and make quantitative comparisons. The measured residual strains and the predictions based on models using optimised parameters showed good agreement. The differences in performance were quantified based on the accuracy of the predicted residual strains, which showed that the Radon transform performed best.
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Research context
OpenAlex topics: Mechanical Behavior of Composites · Ultrasonics and Acoustic Wave Propagation · Optical measurement and interference techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (38)
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