Two inverse methods for turbomachinery blade design are developed. In these inverse design approaches blade shapes are computed for a specified design parameter such as mass-averaged tangential velocity or pressure loading distribution. These inverse methods directly define a geometry needed to obtain these prescribed target design parameters which are related to the performance of turbomachinery blades. The first method is based on the prescription of pressure loading on the blade while the second method is based on the prescription of mass-averaged tangential velocity on the blade. In both methods the blade thickness is also prescribed. These choices of target design prescription allow the designer to control the blade work distribution and the overall flow field effectively. It also prevents the generation of unrealistic blades as the designer directly control the blade thickness. Mesh movement algorithm is an integral part of the current inverse design method as once the blade surface is modified during the design iterations the corresponding unstructured mesh also has to be altered. The mesh movement algorithm is based on a linear tension spring analogy which is a very fast and robust mesh movement method. The capabilities of these design methodologies have been verified for inverse design of two dimensional turbomachinery blades. The flow analysis algorithm is an integral part of the current methodologies. It is based on the incompressible Navier-Stokes flow equations on unstructured meshes. The capability of the flow analysis algorithm is verified for three-dimensional external and internal incompressible flow solutions. Indeed the current method is applied for simulation of flow over marine propeller blades in open water. Also it is applied for the flow analysis of the stator and rotor blades of a low-speed axial turbine.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:692558 |
| Date | January 2006 |
| Creators | Rahmati, M. T. |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/1445805/ |
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