Α deterministic digital twin-based method for damage detection of composites subjected to impact loading: development, validation and time-efficiency improvement using a surrogate model

Abstract

Both monolithic and sandwich composites are highly susceptible to impact loading. Despite of their inherent strength-to-weight ratio benefits, this vulnerability constitutes a major concern related to structural integrity. Although structures designed with fail-safe principles can withstand in theory partial system failure, the early detection of in-service damage is useful for supplementing regular inspections. The development and validation of a time-efficient predictive method for the localization and quantification of damage to composites can bring numerous benefits, such as rapid post-damage strength estimation. In the current study, a deterministic digital twin-based algorithm for the damage localization and quantification of a composite sandwich panel subjected to soft body impact is developed. The effectiveness and robustness of the developed algorithm are highlighted, whilst the time-efficiency of the algorithm is achieved using a kriging surrogate model.