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Research

The main research line of CDIF is based on applied research on Fluid Dynamics and Turbomachines.

The research line is focused on fluid-structure interaction phenomena on both simple (such as disks or plates) and complex geometries (as the turbomachine runner). The acquired knowledge in simple geometries is applied in the study of large scale turbine power generation groups.

The research includes the study of the dynamic excitations generated by the flow and the dynamic response of the structure to these excitations.

Research Line

*Flow visualization obtained in LMH (Laboratory for Hydraulic Machines) in EPFL. 

 

The dynamic response analysis of the structure is of paramount importance in order to avoid excessive vibration and stresses than can lead to a failure.

A hydraulic turbine runner is a complex structure submerged in water, rotating inside an enclosure with very small gaps to the stationary parts. Under these conditions, the added mass and damping effects influence the modal response of the structure, which generates uncertainties when estimating vibration modes, frequencies and amplitude of the vibration phenomena. On the other hand, with the trend of increasing power concentration in generation groups and the trend to work at off-design conditions, the exciting forces over the runner are becoming more intense and unpredictable. Rotor-stator interaction, wake interaction and cavitation have a primal role in the excitation phenomena.


In order to develop the research the following techniques are used:

 

  • Transient flow numerical simulation (CFD) and structural response simulation (FEM)
  • Experimentation in power plants as well as in basic structures and reduced scale models. 
  • Data gathering on real generation groups.
  • Signal analysis for vibration data.
  • AI (Artificial Intelligence) applied on monitored groups.

 

The know-how and experience gathered over the years are applied to the simulation and anaylisis of the vibrational behavior in advance monitoring, damage diagnosis and predicitive maintenance.