DOI: https://doi.org/10.63345/ijrmeet.org.v10.i3.2
Er. Lagan Goel
Director
AKG International
Kandela Industrial Estate, Shamli , U.P., India-247776
Abstract
Finite Element Analysis (FEA) has become an indispensable tool in the design and reliability assessment of wind turbine blades. This manuscript presents a comprehensive, simulation-based investigation into the primary failure mechanisms of composite wind turbine blades under operational and extreme loading conditions, considering technologies and modeling approaches available through 2022. We develop a detailed three-dimensional FEA model of a utility-scale blade, incorporating realistic, anisotropic material properties for glass fiber-reinforced epoxy composites, aerodynamic loading profiles derived from blade element momentum (BEM) theory, and boundary conditions that replicate root constraints and hub interactions. A suite of static, harmonic, and fatigue simulations is conducted across multiple scenarios, including normal operating conditions, 50-year return-period gust events, and lightning strike analogs. To quantify variability, statistical sampling via Latin Hypercube Sampling (LHS) perturbs material elastic moduli and wind speed spectra across 100 trials. We apply Hashin’s failure criteria and cohesive zone models to predict fiber breakage, matrix cracking, and delamination, then use Miner’s rule and S–N curves for damage accumulation. Statistical analysis of the aggregated results yields region-specific failure probabilities, enabling a probabilistic risk assessment. The enhanced simulation workflow identifies leading-edge erosion, spar cap delamination, and root-bending fatigue as dominant failure modes. Insights derived from this study inform design optimization strategies—such as improved erosion-resistant coatings and tailored laminate stacking sequences—and lay the groundwork for integrating digital twin frameworks in predictive maintenance planning.
Keywords
Wind turbine blades; Finite Element Analysis; composite failure; fatigue life; probabilistic simulation
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