Foundation of Digital Twin Reduced-Order Modelling for Laminate Thickness–Stress Analysis in Wind Turbine Blades

Renewable energy sources are expanding rapidly, with wind energy representing one of the fastest-growing sectors. In parallel, digital twins are transforming structural monitoring and inspection by enabling near real-time structural assessment. However, the high computational cost associated with high-fidelity numerical models requires reduced-order or surrogate modelling strategies. Within this context, composite laminate thickness plays a critical role in wind turbine blade design and assessment. In this study, a computational fluid dynamics (CFD)-based numerical model developed in ANSYS was employed to predict von Mises stresses in a three-dimensional wind turbine blade geometry derived from the Carbo4Power project. The numerical results were validated against published literature, enabling identification of a thickness–stress relationship. This foundational analysis supports the development of reduced-order models suitable for digital twin applications in wind turbine blade structural assessment.