This paper presents a procedure for the reliability analysis of a multistage axial compressor regarding blade-specific roughness effects, based on the survival signature approach. As a result, a time-dependent evolution of the system reliability is obtained along with a prioritization technique for monitoring and regeneration of the rough blade rows by capturing the most critical system components. For this purpose, a one-dimensional flow model is developed and utilized to evaluate the aerodynamic influences of the blade-specific roughness on the system performance parameters, namely the overall pressure ratio and the isentropic efficiency. In order to achieve transparency and high numerical efficiency for time-dependent analyses in practice, the physics-based compressor model is translated into an illustrative, function-based system model. This system model is established by conducting a Monte Carlo simulation along with a variance-based global sensitivity analysis, with the input variables being the row-specific blade roughness. Based on the system model, the roughness impact in different blade-rows is ranked by the relative importance (RI) index, and the corresponding time-dependent reliability of the compressor system in terms of pressure ratio and efficiency is estimated through its survival function. Furthermore, uncertainties in the roughness-induced failure rates of the components are modeled using imprecise probabilities. Consequently, bounds on the reliability function and the importance indices for the blade-surface roughness in each blade row are captured, which enhances the decision-making process for maintenance activities under uncertainty.
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September 2019
Research-Article
Reliability Analysis of an Axial Compressor Based on One-Dimensional Flow Modeling and Survival Signature
S. Miro
,
S. Miro
Chair of Mechanics—Continuum Mechanics,
Ruhr-Universität Bochum,
Bochum 44801, Germany
e-mail: shorash.miro@rub.de
Ruhr-Universität Bochum,
Bochum 44801, Germany
e-mail: shorash.miro@rub.de
1Corresponding author.
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T. Willeke
,
T. Willeke
Institute of Turbomachinery and Fluid Dynamics,
Leibniz Universität Hannover,
Hannover 30167, Germany
Leibniz Universität Hannover,
Hannover 30167, Germany
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M. Broggi
,
M. Broggi
Institute for Risk and Reliability,
Leibniz Universität Hannover,
Hannover 30167, Germany
Leibniz Universität Hannover,
Hannover 30167, Germany
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J. R. Seume
,
J. R. Seume
Institute of Turbomachinery and Fluid Dynamics,
Leibniz Universität Hannover,
Hannover 30167, Germany
Leibniz Universität Hannover,
Hannover 30167, Germany
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M. Beer
M. Beer
Institute for Risk and Reliability,
Leibniz Universität Hannover,
Hannover 30167, Germany;
Institute for Risk and Uncertainty,
University of Liverpool,
Liverpool L7 7BD, UK;
International Joint Research Center for
Engineering Reliability and Stochastic Mechanics (ERSM),
Tongji University,
Shanghai 200092, China
Leibniz Universität Hannover,
Hannover 30167, Germany;
Institute for Risk and Uncertainty,
University of Liverpool,
Liverpool L7 7BD, UK;
International Joint Research Center for
Engineering Reliability and Stochastic Mechanics (ERSM),
Tongji University,
Shanghai 200092, China
Search for other works by this author on:
S. Miro
Chair of Mechanics—Continuum Mechanics,
Ruhr-Universität Bochum,
Bochum 44801, Germany
e-mail: shorash.miro@rub.de
Ruhr-Universität Bochum,
Bochum 44801, Germany
e-mail: shorash.miro@rub.de
T. Willeke
Institute of Turbomachinery and Fluid Dynamics,
Leibniz Universität Hannover,
Hannover 30167, Germany
Leibniz Universität Hannover,
Hannover 30167, Germany
M. Broggi
Institute for Risk and Reliability,
Leibniz Universität Hannover,
Hannover 30167, Germany
Leibniz Universität Hannover,
Hannover 30167, Germany
J. R. Seume
Institute of Turbomachinery and Fluid Dynamics,
Leibniz Universität Hannover,
Hannover 30167, Germany
Leibniz Universität Hannover,
Hannover 30167, Germany
M. Beer
Institute for Risk and Reliability,
Leibniz Universität Hannover,
Hannover 30167, Germany;
Institute for Risk and Uncertainty,
University of Liverpool,
Liverpool L7 7BD, UK;
International Joint Research Center for
Engineering Reliability and Stochastic Mechanics (ERSM),
Tongji University,
Shanghai 200092, China
Leibniz Universität Hannover,
Hannover 30167, Germany;
Institute for Risk and Uncertainty,
University of Liverpool,
Liverpool L7 7BD, UK;
International Joint Research Center for
Engineering Reliability and Stochastic Mechanics (ERSM),
Tongji University,
Shanghai 200092, China
Manuscript received September 23, 2018; final manuscript received March 4, 2019; published online June 10, 2019. Assoc. Editor: Gilberto de Souza.
1Corresponding author.
ASME J. Risk Uncertainty Part B. Sep 2019, 5(3): 031003 (9 pages)
Published Online: June 10, 2019
Article history
Received:
September 23, 2018
Revised:
March 4, 2019
Citation
Miro, S., Willeke, T., Broggi, M., Seume, J. R., and Beer, M. (June 10, 2019). "Reliability Analysis of an Axial Compressor Based on One-Dimensional Flow Modeling and Survival Signature." ASME. ASME J. Risk Uncertainty Part B. September 2019; 5(3): 031003. https://doi.org/10.1115/1.4043150
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