Research Papers

Turbine Blade Cooling System Optimization

[+] Author and Article Information
Julian Girardeau

Arts et Metiers ParisTech,
I2M, UMR 5295,
F-33400 Talence, France
F-64511 Bordes, France
e-mail: julian.girardeau@snecma.fr

Jérôme Pailhes

Arts et Metiers ParisTech,
I2M, UMR 5295,
F-33400 Talence, France
e-mail: jerome.pailhes@ensam.eu

Patrick Sebastian

Univ. Bordeaux,
I2M, UMR 5295,
F-33400 Talence, France
e-mail: patrick.sebastian@i2m.u-bordeaux.fr

Frédéric Pardo

F-64511Bordes, France
e-mail: frederic.pardo@turbomeca.fr

Jean-Pierre Nadeau

Arts et Metiers ParisTech,
I2M, UMR 5295,
F-33400 Talence, France
e-mail: jean-pierre.nadeau@ensam.eu

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received August 29, 2012; final manuscript received November 29, 2012; published online September 13, 2013. Editor: David Wisler.

J. Turbomach 135(6), 061020 (Sep 13, 2013) (13 pages) Paper No: TURBO-12-1181; doi: 10.1115/1.4023466 History: Received August 29, 2012; Revised November 29, 2012

Designing high performance cooling systems suitable for preserving the service lifetime of nozzle guide vanes of turboshaft engines leads to significant aerodynamic losses. These losses jeopardize the performance of the whole engine. In the same time, a low efficiency cooling system may affect the costs of maintenance repair and overhaul of the engine as component life decreases. Consequently, designing cooling systems of gas turbine vanes is related to a multiobjective design problem. In this paper, it is addressed by investigating the functioning of a blade and optimizing its design by means of an evolutionary algorithm. Systematic 3D CFD simulations are performed to solve the aero-thermal problem. Then, the initial multiobjective problem is solved by aggregating the multiple design objectives into one single relevant and balanced mono-objective function; two different types of mono-objective functions are proposed and compared. This paper also proposes to enhance available knowledge in the literature of cooling systems of gas turbine vanes by simulating the internal cooling system of the vane. From simulations thermal efficiency and aerodynamic losses are compared and their respective influences on the global performances of the whole engine are investigated. Finally, several optimal designs are proposed.

Copyright © 2013 by ASME
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Müller, S. D., Walther, J. H., and.Koumoutsakos, P.D., 2000, “Evolution Strategies for Film Cooling Optimization,” AIAA J., 39(3), 537–539.
Nowak, G., and Wroblewski, W., 2009, “Cooling System Optimization of Turbine Guide Vane,” Appl. Therm. Eng., 29, pp. 567–572. [CrossRef]
Nowak, G., Wroblewski, W., and Chmielniak, T., 2005, “ Optimization of Cooling Passages Within a Turbine Vane,” ASME Turbo Expo 2005, Reno, NV, June 6–9, ASME Paper No. GT2005-68552. [CrossRef]
Morrone, B., Unich, A., Mariani, A., and DeMaio, V., 2009, “Optimization of a Gas Turbine Stator Nozzle Cooling Using Genetic Algorithms,” Int. Symp. on Heat Transfer in Gas Turbine Systems, Antalya, Turkey, August 9–14.
Ireland, P., and Dailey, G., 2010, Aerothermal Performance of Internal Cooling Systems in Turbomachines ( von Karman Lecture Series), von Karman Institute, Rhode-Saint-Genese, Belgium.
Collignan, A., 2011, “Méthode D'Optimisation et D'aide à la Décision en Conception Mécanique: Application à Une Structure Aéronautique,” Thèse de Doctorat, Université Bordeaux I, Bordeaux, France.
Sebastian, P., Ledoux, Y., Collignan, A., and Pailhes, J., 2012, “Linking Objective and Subjective Modeling in Engineering Design Through Arc-Elastic Dominance,” Expert Systems With Applications, 39(9), pp. 7743–7756. [CrossRef]
Antonsson, E. K., and OttoK. N., 1995, “Imprecision in Engineering Design,” ASME J. Mech. Des., 117, pp. 25–32. [CrossRef]
Schmidt, R. C., and Patankar, S. V., 1991, “Simulating Boundary Layer Transition With Low Reynolds Number k-ε Turbulence Models,” ASME J. Turbomach., 113(1), pp. 10–26. [CrossRef]
Sibulkin, M., 1952, “Heat Transfer Near the Forward Stagnation Point of a Body of Revolution,” J. Aeronaut. Sci., 19(8), pp. 570–571.
Xing, Y., Spring, S., and Weigand, B., 2010, “Experimental and Numerical Investigation of Heat Transfer Characteristics of Inline and Staggered Arrays of Impinging Jets,” ASME J. Heat Transfer, 132(9), p. 092201. [CrossRef]
Haselbach, F., 2008, “HP Turbine Design,” Aero-Engine Design: Form State of the Art Turbofans Towards Innovative Architectures ( von Karman Lecture Series), von Karman Institute, Rhode-Saint-Genese, Belgium.
Cambier, L., and Veuillot, J. P., 2008, “ Status of the elsA CFD Software for Flow Simulation and Multidisciplinary Applications,” AIAA Paper No. 2008-664. [CrossRef]
Hartsel, J. E., 1972, “ Prediction of Effects of Mass-Transfer Cooling on the Blade Row Efficiency of Turbine Airfoils,” ASME Paper. No. 72-11.
Sallee, G. P., 1978, “ Performance Deterioration Based on Existing (Historical) Data, JT9D Jet Engine Diagnostics Program,” Paper No. NASA-CR-135448.
Newell, R., 2010, “ Annual Energy Outlook 2011 Reference Case,” US Energy Information Administration, Washington, DC.
SikorskyS-76C++ Helicopter, Executive Transport Technical Information, 2007, Sikorsky Aircraft Corporation, Stratford, CT.
“Offshore Rig Utilization by Region,” 2012, http://www.rigzone.com.
Conklin & de Decker Aviation Information, 2012, available at http://www.conklindd.com
Harrington, E. C., 1965, “The Desirability Function,” Industrial Quality Control, 21, pp 494–498.
Derringer, G., and Suich, R., 1980, “Simultaneous Optimization of Several Response Variables,” J. Quality Technol., 12(4), pp. 214–219.
Scott, M. J., and Antonsson, E.K., 1995, “Aggregation Functions for Engineering Design Trade-Offs,” 9th International Conference on Design Theory and Methodology, Boston, MA, September 17–20, Vol. 2, pp. 379–396.
Scott, M. J., and Antonsson, E.K., 1998, “Aggregation Functions for Engineering Design Trade-Offs,” Fuzzy Sets Syst., 99(3), pp 253–264. [CrossRef]
Messac, A., Puemi-Sukam, C., and Melachrinoudis, E., 2000, “Aggregate Objective Functions and Pareto Frontiers: Required Relationships and Practical Implications,” Optim. Eng., 1, pp. 171–188. [CrossRef]
Saaty, T. L., 2008, “Relative Measurement and Its Generalization in Decision Making Why Pairwise Comparisons are Central in Mathematics for the Measurement of Intangible Factors the Analytic Hierarchy/Network Process,” Real Academia de Ciencias, 102(2), pp. 251–318. [CrossRef]
Noesis Solutions, 2010, “OPTIMUS Theoretical Background,” Leuven, Belgium.


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Fig. 1

The OIA flow chart

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Fig. 2

Blade and representative slice

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Fig. 3

Design variables related to the trailing edge of the blades

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Fig. 4

Observation model flow chart

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Fig. 5

Blade and inner fluid mesh

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Fig. 6

CFD model boundary conditions

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Fig. 7

Aerothermal problem solving diagram

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Fig. 8

NGV life evolution with maximum metal temperature

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Fig. 9

Impact of dihedral angle on Mach numbers

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Fig. 10

Objective function of the first model

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Fig. 11

Direct maintenance cost

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Fig. 12

Objective function of the second model

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Fig. 13

Harrington's desirability functions

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Fig. 14

Service lifetime desirability function

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Fig. 15

Design exploration results

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Fig. 16

Reference (on top) and optimal solution (on bottom)




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