%0 Generic
%A Tao, Nan
%A Anisimov, Andrei
%A Groves, Roger
%D 2022
%T Shearography data for deep defect detection and characterization in thick GFRP laminates
%U https://data.4tu.nl/articles/dataset/Shearography_data_for_deep_defect_detection_and_characterization_in_thick_GFRP_laminates/21674780/1
%R 10.4121/21674780.v1
%K thick composites
%K shearography
%K Deep defect characterization
%K finite element method (FEM)
%K glass fiber reinforced polymer (GFRP)
%X <p>Thick composite materials, e.g. thickness of more than 50 mm, are increasingly used in a wide variety of industries including aerospace and marine sectors. Nevertheless, defect detection and characterization in these materials remain an appealing challenge. The objective of this research aims at improving deep defect characterization in thick composites with shearography. the raw data (phase-shifted speckle interferograms) are available with the metadata to reproduce the experimental results. Additional interactive videos with the variation of the phase induced by the defects are generated in the dataset</p>
%I 4TU.ResearchData