An abstract approach toward the structural digital twin of ship hulls: A numerical study applied to a box girder geometry

Abstract

Condition monitoring (CM) of ship hull structures is a promising field that has recently attracted the interested of researches. The main challenge behind CM is to develop a system that gets as input sensor readings from the structure and provide the damage locus as an output. In this regard, the current study proposes two alternative CM digital twin schemes for solving this inverse engineering problem. The first one is based on a Finite Element (FE) – Optimization cooperative framework that solves several times the model until the predicted strains match the measured ones and as such the damage location has been found. The other scheme is based on a cooperative framework of Artificial Neural Networks (ANNs) used for classification and fitting, that may be regarded as surrogated models which provide solutions instantaneously. The ANNs are trained through the numerical solutions provided by the FE model. A thin-walled hollow cantilever beam, that resembles a hull-girder subjected to principal stresses under vertical bending, has been adopted. The performed work has allowed for the selection and evaluation of the locations for sensor placement and the estimation of the damage sensitive area for monitoring. Both CM digital twin schemes have proven to be promising for the theoretical simplified examined case.