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Research Papers: Gas Turbines: Turbomachinery

A Reduced Order Modeling Methodology for Steam Turbine Clearance Control Design

[+] Author and Article Information
Emrah Biyik

Department of Energy Systems Engineering,
Yasar University,
Izmir 35100, Turkey
e-mail: emrah.biyik@yasar.edu.tr

Fernando J. D'Amato

GE Global Research,
Niskayuna, NY 12309
e-mail: damato@ge.com

Arun Subramaniyan

Structures Lab,
GE Global Research,
Niskayuna, NY 12309
e-mail: subramaa@ge.com

Changjie Sun

GE Global Research,
Niskayuna, NY 12309
e-mail: sunc@ge.com

Contributed by the Turbomachinery Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received January 11, 2017; final manuscript received February 7, 2017; published online April 11, 2017. Editor: David Wisler.

J. Eng. Gas Turbines Power 139(9), 092604 (Apr 11, 2017) (9 pages) Paper No: GTP-17-1014; doi: 10.1115/1.4036062 History: Received January 11, 2017; Revised February 07, 2017

Finite element models (FEMs) are extensively used in the design optimization of utility scale steam turbines. As an example, by simulating multiple startup scenarios of steam power plants, engineers can obtain turbine designs that minimize material utilization, and at the same time, avoid the damaging effects of large thermal stresses or rubs between rotating and stationary parts. Unfortunately, FEMs are computationally expensive and only a limited amount of simulations can be afforded to get the final design. For this reason, numerous model reduction techniques have been developed to reduce the size of the original model without a significant loss of accuracy. When the models are nonlinear, as is the case for steam turbine FEMs, model reduction techniques are relatively scarce and their effectiveness becomes application dependent. Although there is an abundant literature on model reduction for nonlinear systems, many of these techniques become impractical when applied to a realistic industrial problem. This paper focuses on a class of nonlinear FEM characteristic of thermo-elastic problems with large temperature excursions. A brief overview of popular model reduction techniques is presented along with a detailed description of the computational challenges faced when applying them to a realistic problem. The main contribution of this work is a set of modifications to existing methods to increase their computational efficiency. The methodology is demonstrated on a steam turbine model, achieving a model size reduction by four orders of magnitude with only 4% loss of accuracy with respect to the full order FEMs.

Copyright © 2017 by ASME
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References

Figures

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Fig. 1

Overall reduced order modeling steps

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Fig. 2

Offline reduced order model construction steps

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Fig. 3

Axial displacement errors with modifications M1, M2, and M3

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Fig. 4

Radial displacement errors with modifications M1, M2, and M3

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Fig. 5

Nodal temperatures of the test component for constraint equations

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Fig. 6

Reduced order model validation steps

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Fig. 7

matlab/simulink model for reduced order simulations

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Fig. 8

Cycle deck for reduced order model generation (e.g., steam temperature, pressure, flow, and rotor speed). Actual values and the time scale are omitted due to confidentiality.

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Fig. 10

Stator temperature mismatch between the full order model and the mismatch reduced order model with r = 50 states

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Fig. 9

Rotor temperature mismatch between the full order model and the mismatch reduced order model with r = 50 states

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Fig. 11

Startup cycle deck for ROM validation. Actual values and the time scale are omitted due to confidentiality.

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Fig. 12

Distribution of the mismatch between nodal temperatures in the shell and exhaust hood model

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Fig. 13

Distribution of structural mismatch in the lateral direction (X)

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Fig. 14

Distribution of structural mismatch in the axial direction (Y)

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Fig. 15

Distribution of structural mismatch in the vertical direction (Z)

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