An Ontology-Augmented Digital Twin for Fiber-Reinforced Polymer Structures at the Example of Wind Turbine Rotor Blades

A methodology for establishing a structural digital twin is proposed to facilitate the lifetime prediction of fiber-reinforced polymer (FRP) structures, in this case, a wind turbine rotor blade. The digital twin incorporates production peculiarities and imperfections occurring during the manufacturing process of the FRP component. The methodology involves the computation of process-defined effective elastic properties and residual stresses through numerical simulation of the resin cure cycle. The results are then transferred to a structural finite-element model. By applying local wind conditions to this model, a comprehensive state of stress is obtained. This serves as a basis for a practical evaluation of material fatigue within the composite, leading to the prediction of the component's lifetime. The entire workflow is implemented in a Jupyter-based application that uses an ontology with an appertaining knowledge graph to facilitate the transfer of intermediate results between the observation scales and process steps of the digital twin. In line with the principles of open science, the methodology utilizes open-source software.