Identification of embedded interlaminar flaw using inverse analysis

The integrity of a composite laminate can be greatly affected by an existence of embedded interlaminar flaw. In general, identification of such a flaw often requires expensive tools and tedious processes. The aim of the present work is to develop a novel method with the aid of an intelligent post-processing scheme, thereby not relying on those sophisticated experiments. Essentially the proposed procedure utilizes an inverse analysis to estimate unknown delamination parameters from limited measurements. The procedure first constructs approximate functions relating the delamination parameters to measurement parameters. Then, a multi-dimensional minimization technique is adopted to search for the best estimates of unknown parameters corresponding to the lowest value of error objective function. In the present verification and simulation analyses, surface strains at discrete locations on a composite laminate under three-point bending are selected as the input measurements. Although reasonable estimates are obtained with these measurements, to increase their accuracy, the deflection at load point is also included as measurement input. Additional improvements are observed when those measurements under multiple loading conditions are included. A detailed error sensitivity analysis is also carried out to confirm the method’s robustness. These results suggest the current method to be one of the alternate identification approaches for detecting a single embedded delamination in composite laminates.