Structural Integrity and Loads Assessment

Our ambition is enable reliable design solutions and predictive modeling of large offshore wind turbines and wind farms to improve performance, reduce cost of energy and standardization.

The section focuses on the development of probabilistic methods and applied data science for the reliable design of load-bearing components, as well as assess the integrity of operational turbine components within wind farms such as offshore foundations, bearings and sub-systems such as rotors, drivetrain and support structures.


  • Dynamics
  • Computational mechanics
  • Electro-magnetics
  • Probability & Statistics
  • Reliability
  • System/sub-system modeling
  • Data Science
  • Prognostics
  • Standardization
  • System Identification


  • Design loads prediction
  • Design of support structures
  • Assessment of design conditions
  • Data analytics for decision making
  • Operational planning
  • Assessment of remaining life
  • Recycling of magnets
  • Finite Element Methods
  • Multi-body dynamics-based tools
  • Modal analysis/Operational modal analysis
  • Failure Mode Effect Analysis (FMEA)

Research area & applications

  • Probabilistic integrated design of offshore structures including floating wind turbines, drivetrains and rotors
  • Reliability based wind farm operation for decision support for maintenance, life extension, power uprating, down-rating
  • Artificial Intelligence models for self diagnostics and autonomous/semi-autonomous decision making (machine-to-machine) to enable smart turbines and farms
  • Wind farm upscaling for large scale offshore wind farms including planned maintenance, supply chain prediction and re-powering
  • Wind turbine configuration design and optimization for Power-2-x configurations such as Hydrogen generation and storage

Head of Section

Athanasios Kolios

Athanasios Kolios Professor and Head of Section Mobile: +45 31964956