Towards reliable fatigue life prediction of wind turbines under stochastic wind loads
© Vishnu_Kuniyil
Projektinformationen
eingereicht von
Vishnu Puthukkandi Thazhe Kuniyil
Lehrende
Prof. Dr. Guido Morgenthal, Dr.-Ing. Samir Chawdhury, Dr.-Ing. Sharmistha Chowdhury
Fakultät:
Bau und Umwelt
Studiengang:
Natural Hazards and Risks in Structural Engineering (NHRE) (englischsprachig) (Master of Science (M.Sc.))
Art der Präsentation
Abschlussarbeit
Semester
Sommersemester2025
- Marienstraße 7a
Friday 14:00 to 18:00
Projektbeschreibung
Wind turbines are subjected to complex and highly variable loading conditions due to fluctuating wind speeds and turbulence, making them vulnerable to fatigue damage over time. Accurate prediction of fatigue life is crucial to ensure structural safety, prevent failures, and minimize maintenance costs. However, traditional assessment techniques often oversimplify wind variability, leading to unreliable results.
This project presents a novel methodological framework that incorporates site-specific wind data and turbulence characteristics to improve fatigue life prediction. Using Monte Carlo simulations combined with OpenFAST—an open-source wind turbine simulation tool—this research captures the randomness of wind speed and turbulence intensity.
By simulating a wide range of wind conditions and performing fatigue analysis through rainflow counting and Miner’s rule, the study enables a comprehensive parametric investigation. The entire process is automated to ensure efficiency and scalability. This approach offers a deeper understanding of how wind variability influences fatigue damage and aims to provide a more reliable and cost-effective strategy for wind turbine design and maintenance planning.