Abbas Kazemi Amiri is a researcher specialising in structural dynamics, vibration-based analysis and lifetime assessment of large-scale wind energy structures. His work combines advanced signal processing, inverse methods and physical modelling to infer loads and structural behaviour from limited measurement data.

A central aspect of his research is the identification of dynamic loads acting on wind turbine towers and support structures using inverse techniques. Rather than relying solely on direct load measurements, his approaches reconstruct excitation forces from measured responses, enabling load estimation in situations where direct sensing is impractical or unavailable.

This work relies on a strong grounding in structural dynamics, including modal analysis, frequency-domain and time-domain identification methods. Operational modal analysis techniques are used to characterise structural behaviour under ambient and operational loading, supporting the identification of changes in dynamic properties over time.

Abbas has applied these methods to fatigue and lifetime assessment of wind turbine structures, linking estimated load histories with damage accumulation models. This enables condition-informed evaluation of remaining life and supports decisions related to inspection, life extension and structural reinforcement.

His research also contributes to vibration-based condition monitoring, where changes in dynamic response are used to detect damage or degradation. The emphasis is on physically interpretable indicators that can be related back to structural behaviour rather than purely data-driven features.

---

Key expertise

• Structural dynamics and vibration analysis of wind turbine towers
• Inverse load identification using measured structural responses
• Operational modal analysis under ambient and operational excitation
• Fatigue and lifetime assessment of large-scale structures
• Vibration-based condition monitoring and damage detection

Abbas Kazemi Amiri’s work strengthens WECC’s capability in structural integrity assessment, enabling data-informed evaluation of loads, fatigue and remaining life for wind energy assets operating under complex and variable conditions.