Aerothermal optimization and experimental verification for discrete turbine airfoil film cooling

C. El Ayoubi, W. S. Ghaly, Ibrahim Hassan

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The optimization aims to maximize the film cooling performance while minimizing the corresponding aerodynamic penalty. The cooling performance is assessed using the adiabatic film cooling effectiveness, while the aerodynamic penalty is measured with a mass-averaged total pressure loss coefficient. Two design variables are selected: the coolant-to-mainstream temperature ratio and the coolant-to-mainstream total pressure ratio. Two staggered rows of discrete cylindrical film cooling holes on the suction surface of a turbine vane are considered.Anondominated sorting genetic algorithm (NSGA-II) is coupled with an artificial neural network (ANN) to perform a multiple-objective optimization of the coolant flow parameters on the vane suction surface. Three-dimensional Reynolds-averaged Navier-Stokes (RANS) simulations are employed to construct the ANN network that produces low-fidelity predictions of the objective functions during the optimization. The effect of varying the coolant flow parameters on the adiabatic film cooling effectiveness and the aerodynamic loss is analyzed using the optimization method and RANS simulations. The computational fluid dynamics predictions of the adiabatic film cooling effectiveness and aerodynamic performance are assessed and validated against corresponding experimental measurements. The optimal solutions are reproduced in the experimental facility and the Pareto front is substantiated with experimental data.

Original languageEnglish
Pages (from-to)543-558
Number of pages16
JournalJournal of Propulsion and Power
Volume31
Issue number2
DOIs
Publication statusPublished - 2015
Externally publishedYes

Fingerprint

film cooling
airfoils
turbines
Airfoils
turbine
coolants
Turbines
aerodynamics
Cooling
cooling
Coolants
optimization
Aerodynamics
vanes
suction
penalties
artificial neural network
sorting algorithms
temperature ratio
pressure ratio

ASJC Scopus subject areas

  • Aerospace Engineering
  • Space and Planetary Science
  • Fuel Technology
  • Mechanical Engineering

Cite this

Aerothermal optimization and experimental verification for discrete turbine airfoil film cooling. / El Ayoubi, C.; Ghaly, W. S.; Hassan, Ibrahim.

In: Journal of Propulsion and Power, Vol. 31, No. 2, 2015, p. 543-558.

Research output: Contribution to journalArticle

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