There are several methods for enhancing the efficiency of the Vertical Axis Turbine (VAT) and Oscillating Foil Turbine (OFT), such as the variable pitch method for the VAT blade and the non-sinusoidal pitch method for the OFT. However, all of them are not bio-inspired methods. The main objective of the present research is to develop innovative methods to enhance the efficiency of a renewable turbine by using bio-inspired flow controls. In the present research, bio-inspired methods are used to modify the traditional rigid turbine blade such as the active and passive flow controlled flaps for VAT which are inspired by the fishtail motion and the active and passive blade flexibility for OFT which is inspired by butterfly wings. Simulations are carried out by solving 2D/3D Navier-Stokes equations either by themselves or fully coupled with a finite element structure solver at both laminar and turbulent flow conditions. The results show energy extraction efficiency enhancement effects by using bio-inspired flow controlled methods for both VAT and OFT under certain conditions. The mechanics of bio-inspired flow control, such as vortex control for VAT using an active or passive oscillating flap, force enhancement and phase shift effects of active flow controlled OFT and LEV control for passive flow controlled OFT, are also studied. Previous research studies on the HAT show a blade stress reduction effect and longer life cycles by using composite material or Morphing Blade (MB). However, not much is known about the performance and function of the composite material regarding VAT. The present study on the passive flow controlled spanwise flexible blade of VAT shows the blade structural characteristics associated with bending and twist deflection as sinusoidal functions. The blade external unsteady loads and the power performance of VAT are first studied, which have been further extended to a blade stress analysis.
|Date of Award||29 Nov 2015|
- University Of Strathclyde
|Sponsors||University of Strathclyde|
|Supervisor||Qing Xiao (Supervisor) & Atilla Incecik (Supervisor)|