Deformation Based Multiaxial Cycle Counting for the Progressive Damage Analysis of Wind Turbine Blades

ABSTRACT

The structural integrity of wind turbine blades depends critically on accurate predictions of the stiffness degradation under complex, multiaxial loading. Traditional fatigue assessments often rely on uniaxial rainflow counting coupled with linear damage accumulation. However, these approaches fail to capture the progressive stiffness reduction inherent to composite materials under multiaxial loading.

Conventional multiaxial counting methods, such as critical plane and equivalent stress formulations, require a known stress history. However, in the presence of stiffness degradation, the stress state evolves continuously, creating an implicit dependency on the cycle count that renders these stress‐based methods invalid. This study addresses alternative deformation‐based projection methods, specifically deterministic hypersphere sampling (Super‐Fibonacci) and singular value decomposition, using synthetic time histories of the blade deformation data resulting from beam simulations of a stochastic wind field.

The resulting cycle blocks are applied to a three‐dimensional shell model of a state‐of‐the‐art blade. Unlike standard fatigue life predictions, this framework combines the counting outputs directly with a progressive damage model to account for the non‐linear evolution of damage. The analysis focuses on the correlation between the chosen counting method and the stiffness degradation of critical sections. The study demonstrates that counting strategies based on uniform spatial projections better capture more severe, multiaxial degradation than simple component‐wise decomposition methods and offer a method of decoupling the cycle counting from the stress evolution in composite fatigue analysis.