14, Data-Driven Structural Analysis of Geometrically Exact Beams with Application to Wind Turbine Blades
Data-Driven Computational Mechanics (DDCM) offers an alternative to conventional constitutive modeling by replacing constitutive equations with material datasets embedded directly into the solution process. While DDCM has been successfully applied to a variety of mechanical problems, its application to large-scale rotating beam structures remains largely unexplored. Building upon the framework of [1], we extend the Discrete-Continuous Nonlinear Optimization Problem to geometrically exact beams subject to configuration-dependent loading and incorporate rotational inertia effects and centrifugal stiffening. The proposed methodology is verified through a series of benchmark problems involving large rotations, three-dimensional loading conditions, and rotating beam eigenvalue analyses. Subsequently, the framework is applied to the NREL 5 MW wind turbine blade subjected to aerodynamic loads and prescribed rotor motion. The results demonstrate excellent agreement between the discrete-continuous nonlinear optimization problem and approximate nonlinear optimization problem formulations for deformed configurations, blade-tip displacements, strain fields, and stress fields. Furthermore, our study highlights the influence of constitutive dataset density on solution accuracy and indicates that, for the numerical examples considered, global structural quantities converge more rapidly with increasing dataset density than local constitutive variables.