Development of Shape-Optimization Tools for the Aerodynamic Design of Turbomachinery Blades

Rodriguez-Fernandez, Pablo (2015). Development of Shape-Optimization Tools for the Aerodynamic Design of Turbomachinery Blades. Proyecto Fin de Carrera / Trabajo Fin de Grado, E.T.S.I. Industriales (UPM).

Descripción

Título: Development of Shape-Optimization Tools for the Aerodynamic Design of Turbomachinery Blades
Autor/es:
  • Rodriguez-Fernandez, Pablo
Director/es:
  • Prieto Ortiz, Juan Luis
  • Persico, Giacomo Bruno
Tipo de Documento: Proyecto Fin de Carrera/Grado
Fecha: 12 Marzo 2015
Materias:
Palabras Clave Informales: Shape-Optimization, Blade, Optimization, Genetic, Evolutionary, Algorithm, Metamodel, ORC
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Ingeniería Energética
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The aim of this work is to develop an automated tool for the optimization of turbomachinery blades founded on an evolutionary strategy. This optimization scheme will serve to deal with supersonic blades cascades for application to Organic Rankine Cycle (ORC) turbines. The blade geometry is defined using parameterization techniques based on B-Splines curves, that allow to have a local control of the shape. The location in space of the control points of the B-Spline curve define the design variables of the optimization problem. In the present work, the performance of the blade shape is assessed by means of fully-turbulent flow simulations performed with a CFD package, in which a look-up table method is applied to ensure an accurate thermodynamic treatment. The solver is set along with the optimization tool to determine the optimal shape of the blade. As only blade-to-blade effects are of interest in this study, quasi-3D calculations are performed, and a single-objective evolutionary strategy is applied to the optimization. As a result, a non-intrusive tool, with no need for gradients definition, is developed. The computational cost is reduced by the use of surrogate models. A Gaussian interpolation scheme (Kriging model) is applied for the estimated n-dimensional function, and a surrogate-based local optimization strategy is proved to yield an accurate way for optimization. In particular, the present optimization scheme has been applied to the re-design of a supersonic stator cascade of an axial-flow turbine. In this design exercise very strong shock waves are generated in the rear blade suction side and shock-boundary layer interaction mechanisms occur. A significant efficiency improvement as a consequence of a more uniform flow at the blade outlet section of the stator is achieved. This is also expected to provide beneficial effects on the design of a subsequent downstream rotor. The method provides an improvement to gradient-based methods and an optimized blade geometry is easily achieved using the genetic algorithm.

Más información

ID de Registro: 34960
Identificador DC: http://oa.upm.es/34960/
Identificador OAI: oai:oa.upm.es:34960
Depositado por: Pablo Rodriguez-Fernandez
Depositado el: 20 Abr 2015 14:40
Ultima Modificación: 20 Abr 2015 14:40
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