Semester of Graduation
Fall 2024
Degree
Master of Science in Civil Engineering (MSCE)
Department
Civil and Environmental Engineering
Document Type
Thesis
Abstract
This thesis presents an integrated approach for predicting the fatigue life of wind turbine blades, combining the aeroelastic simulation capabilities of OpenFAST with the detailed structural analysis offered by ANSYS. The method combines turbulent wind profile generation using TurbSim, aeroelastic simulations in OpenFAST, and high-fidelity structural analysis in ANSYS. By simulating the effects of varying wind speeds (7 m/s, 12.55 m/s, and 15 m/s), the thesis demonstrates how increasing wind speeds lead to higher stress concentrations in the midsection of the blade, significantly reducing its fatigue life. The use of ANSYS for fatigue life predictions, validated against Sandia National Laboratories (SNL) experimental data, demonstrates ANSYS high efficiency and remarkable accuracy in predicting fatigue life. Simulation results reveal critical insights into fatigue performance, showing that higher wind speeds increase stress concentrations, especially at the blade midsection, significantly reducing fatigue life. The use of Miner’s rule enabled a detailed analysis of cumulative damage, showing that the midsection of the blade is highly vulnerable to fatigue failure after prolonged exposure to high wind conditions. The cumulative fatigue damage calculated for these areas is 0.99, indicating that the blade is close to failure. The thesis also compares the OpenFAST-ANSYS approach with the Power Law, showing strong agreement in fatigue life predictions across all wind conditions. This demonstrates the robustness and accuracy of the integrated methodology, offering a reliable and cost-effective alternative to traditional full-scale testing for wind turbine blades. These findings emphasize the importance of design reinforcements in stress-prone areas and provide critical insights for optimizing blade design, improving durability, and reducing maintenance costs. The conclusions drawn from this work are vital for enhancing the operational life of wind turbines and supporting the continued growth of wind energy as a sustainable power source.
Date
11-1-2024
Recommended Citation
AlShannaq, Husam, "PREDICTING FATIGUE IN WIND TURBINE BLADES: AN INTEGRATED APPROACH USING OPENFAST AND ANSYS" (2024). LSU Master's Theses. 6057.
https://repository.lsu.edu/gradschool_theses/6057
Committee Chair
Aly, Aly