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Bayesian Inverse Transient Analysis for Pipeline Condition Assessment: Parameter Estimation and Uncertainty Quantification

Author

Listed:
  • Chi Zhang

    (University of Adelaide)

  • Martin F. Lambert

    (University of Adelaide)

  • Jinzhe Gong

    (University of Adelaide
    Deakin University)

  • Aaron C. Zecchin

    (University of Adelaide)

  • Angus R. Simpson

    (University of Adelaide)

  • Mark L. Stephens

    (Asset Analytics Lead; Asset Management Department)

Abstract

Strategic pipeline asset management requires accurate and up-to-date information on pipeline condition. As a tool for pipeline condition assessment, inverse transient analysis (ITA - a pipeline model calibration approach) is typically formulated as a deterministic problem, and optimization methods are used for searching a single best solution. The uncertainty associated with the single best solution is rarely assessed. In this paper, the pipeline model calibration problem is formulated as a Bayesian inverse problem, and a Markov Chain Monte Carlo (MCMC) based method is used to construct the estimated posterior probability density function (PDF) of the calibration parameters. The MCMC based method is able to achieve parameter estimation and uncertainty assessment in a single run, which is confirmed by numerical experiments. The proposed technique is also validated using measured hydraulic transient response data from an experimental laboratory pipeline system. Two thinner-walled pipe sections (simulating extended deterioration) are successfully identified with an assessment of the parameter uncertainty. The results also suggest that proper sensor placement can reduce parameter uncertainty and significantly enhance system identifiability.

Suggested Citation

  • Chi Zhang & Martin F. Lambert & Jinzhe Gong & Aaron C. Zecchin & Angus R. Simpson & Mark L. Stephens, 2020. "Bayesian Inverse Transient Analysis for Pipeline Condition Assessment: Parameter Estimation and Uncertainty Quantification," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2807-2820, July.
    • Handle: RePEc:spr:waterr:v:34:y:2020:i:9:d:10.1007_s11269-020-02582-9
    DOI: 10.1007/s11269-020-02582-9
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    References listed on IDEAS

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    1. Huan-Feng Duan, 2018. "Accuracy and Sensitivity Evaluation of TFR Method for Leak Detection in Multiple-Pipeline Water Supply Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(6), pages 2147-2164, April.
    2. Silvia Meniconi & Bruno Brunone & Marco Ferrante & Christian Massari, 2011. "Small Amplitude Sharp Pressure Waves to Diagnose Pipe Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(1), pages 79-96, January.
    3. Chi Zhang & Jinzhe Gong & Martin F. Lambert & Angus R. Simpson & Aaron C. Zecchin, 2019. "Sensor Placement Strategy for Pipeline Condition Assessment Using Inverse Transient Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(8), pages 2761-2774, June.
    4. Aditya Gupta & K. D. Kulat, 2018. "A Selective Literature Review on Leak Management Techniques for Water Distribution System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3247-3269, August.
    5. Ali Haghighi & Helena Ramos, 2012. "Detection of Leakage Freshwater and Friction Factor Calibration in Drinking Networks Using Central Force Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(8), pages 2347-2363, June.
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    Cited by:

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