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Multi-objective optimization of 3D film cooling configuration with thermal barrier coating in a high pressure vane based on CFD-ANN-GA loop

  • Ali Reza Mostofizadeh
  • Mahmud Adami
  • Mohammad Hossein Shahdad
Technical Paper
  • 65 Downloads

Abstract

In this paper, the optimum parameters of a row of cylindrical film cooling holes have been investigated using a multi-objective evolutionary approach so as to achieve a compromise between film cooling effectiveness and coolant mass flow rate which are in opposite directions and compete with each other. For this purpose, chord-wise position of film holes as well as diameter and injection angles and holes spacing were chosen as design parameters. Forty samples were generated as database through CFD runs; artificial neural network (ANN) method was used to construct the surrogate model to approximate the optimization targets as functions of design parameters and genetic algorithm (GA) was used as optimizer. Design iterations were repeated seven times through the mentioned CFD-ANN-AG loop and optimum configuration, including film holes spacing, diameter, injection position and angle, based on objective function values was found. However, added row imposed an excess amount of coolant mass flow rate through the vane cavity which had a negative impact on the engine performance. Therefore, at last part of this work a thermal barrier coating layer was applied on external surfaces of the vane in order to assess the possibility of decreasing coolant mass flow rate with no additional increase on its exerted thermal loads.

Keywords

Artificial neural network (ANN) Computational fluid dynamics (CFD) Conjugate heat transfer (CHT) Film cooling Turbine blade Genetic algorithm (GA) Multi-objective optimization Thermal barrier coating (TBC) 

List of symbols

η

Film cooling effectiveness

\(\dot{m}\)

Mass flow

T

Temperature

Z

Span-wise direction

Xi

Spatial coordinates

ρ

Density

ui

Velocity components

P

Pressure

\(\rho \overline{{u_{i}^{'} u_{j}^{'} }}\)

Reynolds stress components

E

Energy

k

Turbulent kinetic energy

ε

Turbulent energy dissipation

ω

Rate of turbulent energy dissipation

μt

Turbulent eddy viscosity

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Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2018

Authors and Affiliations

  • Ali Reza Mostofizadeh
    • 1
  • Mahmud Adami
    • 1
  • Mohammad Hossein Shahdad
    • 1
  1. 1.Department of Mechanical EngineeringMalek-Ashtar University of TechnologyEsfahanIran

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