• Net salary: approximately €3,000/month (for 36 months)
• Starting date: November 1, 2026

Project title: Self-tuning Variable Length Systems for the Vibration Reduction of Wind Turbine Blades

Project description: The aim of this research is to develop and analyze self-tuning Variable Length Systems (VLS) for reducing wind turbine blade vibrations. The study will focus on deriving a dimensionless formulation of the differential-algebraic system governing the nonlinear dynamics of lumped-mass VLS subjected to configurational forces. 
A perturbation-based approach will be employed to identify the self-tuning curve and to perform a parametric analysis with respect to variations in the stiffness of the additional elastic constraint. The project will also address the space–time integration of the nonlinear differential-algebraic equations of motion, the investigation of limit cycle behavior, and the evaluation of the frequency range over which self-tuning occurs. 
Finally, the optimal number and placement of VLS along the wind turbine blade will be investigated, and their effectiveness in reducing vibrations will be assessed, with particular attention to improvements in high-cycle fatigue performance.

Secondment periods are planned at the project’s partner institutions.

Reference:  Koutsogiannakis, P., Misseroni, D., Bigoni, D., Dal Corso, F. (2023). Stabilization against gravity and self-tuning of an elastic variable-length rod through an oscillating sliding sleeve. Journal of the Mechanics and Physics of Solids, 181: 105452.

Candidate requirements:

• By July 10, 2026, applicants must hold a Master’s degree (or an equivalent second-cycle qualification) in Civil or Mechanical Engineering (or a related field), qualifying them for admission to a PhD program.
• The degree must have been obtained no more than six years before July 10, 2026.
• Have not yet been awarded a doctoral degree.

 

While the application must be submitted online through a link that will be available shortly, please encourage interested candidates to contact Prof. Francesco Dal Corso (francesco.dalcorso@unitn.it) in advance.