Quantitative defect detection in composite structures is an important problem as the aerospace and wind energy industries are increasingly using composites due to their attractive properties. Newer aircraft contain over 50% composites, while the wind turbine blades contain over 95% composites. Quantitative estimation of defect parameters is relevant to perform repairs and assess the integrity of these structures. Previous studies are based on simple 1D heat conduction models, which are inadequate in predicting heat flow around defects, especially in composites where the ratio of longitudinal to transverse thermal conductivity is about 100. In this study, a novel heat conduction model is proposed to model heat flow around defects accounting for 3D heat conduction in quasi-isotropic composites. The validity of the proposed methodology is established using experiments performed on a CFRP panel containing defects of different dimensions at different depths. The inverse problem could be used to quantitatively determine the defect depth and size.

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