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Assessment of Material Durability of Steam Pipelines Based on Statistical Analysis of Strength Properties—Selected Models

Author

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  • Jarosław Piątkowski

    (Department of Material Science, Silesian University of Technology, 40-019 Katowice, Poland)

  • Bożena Gajdzik

    (Department of Industrial Informatics, Silesian University of Technology, 40-019 Katowice, Poland)

  • Aleksander Mesjasz

    (Group Tauron, 43-603 Jaworzono, Poland)

Abstract

The paper presents a research method concerning the application of statistical prognostic models for assessment of material durability and operational reliability of steel for steam pipelines, whose operation has exceeded the working time of 100,000 h. Decisions on the admission of long-lived materials to work for power industry results from extensive diagnostic examinations are based on the results of tests of mechanical properties, microstructure degradation, and corrosion processes. Considering the economic reasons and available data published in diagnostic reports, the determination of failure-free operating time of steam pipelines is based on the results of static tensile tests—tensile strength ( R m ); conventional yield point ( R p ); elongation ( A ) and Vickers hardness ( V ), correlated with the operating time and the media type (fresh steam and secondarily super-heated steam) for the most sensitive element of a pipeline, namely the elbow. The results of changes in strength properties during operation are presented in the form of graphs of the analyzed material feature vs. operating time in the range from zero hours (for a new material) to 300,000 h, taking into account the impact of random and systematic disturbances within the adopted tolerance limits. It has been found that because of the R 2 factor and significance level in the t -Student test for regression and correlation coefficients, exponential, hyperbolic and quadratic models are best fitted to empirical points. Based on the tensile strength results ( R m ), it has been found that the forecast time of the steam pipeline ranges from 193,400 to 258,300 h. Taking the yield strength ( R p ) into account, it has been ascertained that the time ranges from 225,000 to 293,000 h, and for the working time forecast of steam pipelines based on Vickers hardness results, it ranges from 192,100 to 246,800 h.

Suggested Citation

  • Jarosław Piątkowski & Bożena Gajdzik & Aleksander Mesjasz, 2020. "Assessment of Material Durability of Steam Pipelines Based on Statistical Analysis of Strength Properties—Selected Models," Energies, MDPI, vol. 13(14), pages 1-18, July.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3633-:d:384481
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    References listed on IDEAS

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    1. McCarthy, Ryan W. & Ogden, Joan M. & Sperling, Daniel, 2007. "Assessing reliability in energy supply systems," Energy Policy, Elsevier, vol. 35(4), pages 2151-2162, April.
    2. Balakrishnan, N. & Kateri, M., 2008. "On the maximum likelihood estimation of parameters of Weibull distribution based on complete and censored data," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2971-2975, December.
    3. Rusin, Andrzej & Bieniek, Michał, 2017. "Maintenance planning of power plant elements based on avoided risk value," Energy, Elsevier, vol. 134(C), pages 672-680.
    4. Zhong, Wei & Feng, Hongcui & Wang, Xuguang & Wu, Dingfei & Xue, Minghua & Wang, Jian, 2015. "Online hydraulic calculation and operation optimization of industrial steam heating networks considering heat dissipation in pipes," Energy, Elsevier, vol. 87(C), pages 566-577.
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