A Reduced Order Modeling Methodology for Steam Turbine Clearance Control Design
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Date
2017
Authors
Emrah Biyik
Fernando J. D'Amato
Arun Subramaniyan
Changjie Sun
Journal Title
Journal ISSN
Volume Title
Publisher
ASME
Open Access Color
Green Open Access
Yes
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Publicly Funded
No
Abstract
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.
Description
Keywords
model reduction, steam turbine, clearance control, nonlinear models, proper orthogonal decomposition, REDUCTION, SYSTEMS
Fields of Science
0209 industrial biotechnology, 02 engineering and technology, 0101 mathematics, 01 natural sciences
Citation
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OpenCitations Citation Count
2
Source
Journal of Engineering for Gas Turbines and Power
Volume
139
Issue
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CrossRef : 1
Scopus : 4
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