Research Papers

Optimization Strategy for a Coupled Design of the Last Stage and the Successive Diffuser in a Low Pressure Steam Turbine

[+] Author and Article Information
Christian Musch

e-mail: christian.musch@siemens.com

Heinrich Stüer

e-mail: heinrich.stueer@siemens.com
Siemens AG,
Energy Sector,
45478 Mülheim an der Ruhr, Germany

Georg Hermle

University of Kassel,
Department of Turbomachinery,
34109 Kassel, Germany
e-mail: georg.hermle@uni-kassel.de

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) Division of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received July 25, 2011; final manuscript received August 3, 2011; published online November 6, 2012. Editor: David Wisler.

J. Turbomach 135(1), 011013 (Nov 06, 2012) (7 pages) Paper No: TURBO-11-1159; doi: 10.1115/1.4006335 History: Received July 25, 2011; Revised August 03, 2011

In this study, an effective yet numerically simple approach for a coupled design of the last stage running blade and diffuser is presented. The method applied uses a two-dimensional streamline curvature code combined with a boundary layer solver for the prediction of flow separation within the diffuser. An accurate representation of the diffuser flow is vital for the assessment of the overall performance. Thus, the major influences from the turbine stage on the diffuser flow, i.e., the tip leakage jet and the swirl of the flow, are taken into account. Secondary effects like blade wakes are neglected. The basic capability of the method to correctly represent the flow is demonstrated by a comparison with three-dimensional CFD simulations of a sample configuration. Solid correlation can be found between both cases. For the optimization process, a genetic algorithm is used. Optimization parameters include the blade exit angle and the diffuser contour. The results of the optimization are again scrutinized with the assistance of three-dimensional CFD simulations.

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Fig. 3

Boundary layer profiles of wall jet

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Fig. 2

Velocity profiles of wall jet

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Fig. 1

Wall jet acc. to Schlichting [12]

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Fig. 4

Test diffuser arrangement

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Fig. 5

Wall jet with pressure gradient

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Fig. 6

Flow domain of 3D-CFD

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Fig. 13

Pressure recovery and efficiency

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Fig. 10

2D-flowpath: optimized versus datum

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Fig. 11

BL solver versus 3D-CFD (optimized design)

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Fig. 12

SLEQ versus 3D-CFD (optimized design)

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Fig. 7

SLEQ versus 3D-CFD (datum design)

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Fig. 8

BL solver versus 3D-CFD (datum design)

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Fig. 9

2D-flowpath and diffuser parameters




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