Reliability Analysis of an Axial Compressor Based on One-Dimensional Flow Modeling and Survival Signature

Research output: Contribution to journalArticleResearchpeer review

Authors

  • S. Miro
  • Tobias Willeke
  • Matteo Broggi
  • Jörg Reinhart Seume
  • Michael Beer

External Research Organisations

  • Ruhr-Universität Bochum
  • University of Liverpool
  • Tongji University
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Details

Original languageEnglish
Article number031003
JournalProcedia CIRP
Volume5
Issue number3
Publication statusPublished - 10 Jun 2019

Abstract

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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Cite this

Reliability Analysis of an Axial Compressor Based on One-Dimensional Flow Modeling and Survival Signature. / Miro, S.; Willeke, Tobias; Broggi, Matteo et al.
In: Procedia CIRP, Vol. 5, No. 3, 031003, 10.06.2019.

Research output: Contribution to journalArticleResearchpeer review

Miro S, Willeke T, Broggi M, Seume JR, Beer M. Reliability Analysis of an Axial Compressor Based on One-Dimensional Flow Modeling and Survival Signature. Procedia CIRP. 2019 Jun 10;5(3):031003. doi: 10.1115/1.4043150
Miro, S. ; Willeke, Tobias ; Broggi, Matteo et al. / Reliability Analysis of an Axial Compressor Based on One-Dimensional Flow Modeling and Survival Signature. In: Procedia CIRP. 2019 ; Vol. 5, No. 3.
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title = "Reliability Analysis of an Axial Compressor Based on One-Dimensional Flow Modeling and Survival Signature",
abstract = "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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