Research Papers

Coupled Aerothermodynamics Optimization for the Cooling System of a Turbine Vane

[+] Author and Article Information
Zhongran Chi

e-mail: ccr11@mails.tsinghua.edu.cn

Hongde Jiang

Department of Thermal Engineering,
Tsinghua University,
Beijing 100084, China

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received June 23, 2013; final manuscript received July 7, 2013; published online September 27, 2013. Editor: Ronald Bunker.

J. Turbomach 136(5), 051008 (Sep 27, 2013) (11 pages) Paper No: TURBO-13-1107; doi: 10.1115/1.4025178 History: Received June 23, 2013; Revised July 07, 2013

The cooling system design for air-cooled turbines is a critical issue in modern gas turbine engineering. Advances in the computational fluid dynamics (CFD) technology and optimization methodology are providing new prospects for turbine cooling system design, in the sense that the optimum cooling system of the vanes and blades could be designed automatically by the optimization search coupled with the full three-dimensional conjugate heat transfer (CHT) analysis. An optimization platform for air-cooled turbines, which consists of the genetic algorithm (GA), a mesh generation tool (Coolmesh), and a CHT solver is presented in this paper. The optimization study was aimed at finding the optimum cooling structure for a 2nd stage vane with, simultaneously, an acceptable metal temperature distribution and limited amount of coolant. The vane was installed with an impingement and pin-fin cooling structure. The optimization search involved the design of the critical parameters of the cooling system, including the size of the impingement tube, diameter and distribution of impingement holes, and the size and distribution of the pin-fin near trailing edge. The design optimization was carried out under two engine operating conditions in order to explore the effects of different boundary conditions. A constant pressure drop was assumed within the cooling system during each optimization. To make the problem computationally faster, the simulations were approached for the interior only (solid and coolant). A weighted function of the temperature distribution and coolant mass flow was used as the objective of the single objective genetic algorithm (SOGA). The result showed that the optimal cooling system configuration with considerable cooling performance could be designed through the SOGA optimization without human interference.

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Fig. 1

Profile of the turbine stage

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Fig. 2

Internal cooling structure of the vane

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Fig. 3

The CHT mesh of the vane cooling system

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Fig. 4

Results of mesh quality checking

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Fig. 5

Principle of TLC measurements

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Fig. 6

Test facility: (a) configuration of the test rig, (b) assembly of the test section, and (c) the CCD image

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Fig. 7

The CFD results (squares) and TLC data (filled circles) of the surface-averaged Nu

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Fig. 8

The CFD results (lines) and TLC data (dots) of the spanwise-averaged Nu

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Fig. 9

The CHT mesh of the Mark-II vane

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Fig. 10

Comparison of the CHT CFD results (lines) and experimental data (filled circles) of the Mark-II vane at the midspan section of the vane surface: (a) pressure, and (b) blade temperature

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Fig. 11

Boundary conditions

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Fig. 12

Radial distributions of the total temperature at the inlet

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Fig. 13

Heat transfer boundary conditions for the CHT runs: (a) total temperature of hot gas at midspan, and (b) convective heat transfer coefficient at midspan

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Fig. 14

Optimization flow chart

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Fig. 15

Run history of the GA optimization search for Run no. 1 and Run no. 2

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Fig. 16

Optimal scheme found by the GA for Condition no. 1: (a) cooling structure, (b) temperature distribution on the outer surface, and (c) heat flux distribution on the internal surface

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Fig. 17

Optimal scheme found by the GA for Condition no. 2: (a) cooling structure, (b) temperature distribution on the outer surface, and (c) heat flux distribution on the internal surface

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Fig. 18

Relationship between the coolant amount and the average wall temperature of individuals




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