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Adjoint operator approach to functional reliability analysis of passive fluid dynamical systems

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  • Arul, A. John
  • Iyer, N. Kannan
  • Velusamy, K.

Abstract

Reliability analysis of passive systems mainly involves quantification of the margin to safety limits in probabilistic terms. For systems represented by complex models, propagating input uncertainty to get the response uncertainty and hence probability information requires intensive computational effort. Here a computationally efficient method for the functional reliability analysis of passive fluid dynamical systems is presented. The approach is based on continuous adjoint operator technique to generate a response surface approximating the given system model from the sensitivity coefficients. A numerical application of this method to the reliability analysis of heat transport in an asymmetrical natural convection loop is demonstrated. Computational efficiency and accuracy compared with the direct Monte-Carlo and forward response surface methods.

Suggested Citation

  • Arul, A. John & Iyer, N. Kannan & Velusamy, K., 2009. "Adjoint operator approach to functional reliability analysis of passive fluid dynamical systems," Reliability Engineering and System Safety, Elsevier, vol. 94(12), pages 1917-1926.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:12:p:1917-1926
    DOI: 10.1016/j.ress.2009.06.008
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    References listed on IDEAS

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    1. Marseguerra, M. & Zio, E. & Podofillini, L., 2005. "First-order differential sensitivity analysis of a nuclear safety system by Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 90(2), pages 162-168.
    2. Burgazzi, Luciano, 2007. "Thermal–hydraulic passive system reliability-based design approach," Reliability Engineering and System Safety, Elsevier, vol. 92(9), pages 1250-1257.
    3. Zio, E. & Pedroni, N., 2009. "Functional failure analysis of a thermal–hydraulic passive system by means of Line Sampling," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1764-1781.
    4. Durga Rao, K. & Kushwaha, H.S. & Verma, A.K. & Srividya, A., 2007. "Quantification of epistemic and aleatory uncertainties in level-1 probabilistic safety assessment studies," Reliability Engineering and System Safety, Elsevier, vol. 92(7), pages 947-956.
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    Cited by:

    1. Zio, E. & Pedroni, N., 2012. "Monte Carlo simulation-based sensitivity analysis of the model of a thermal–hydraulic passive system," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 90-106.
    2. Francesco Di Maio & Nicola Pedroni & Barnabás Tóth & Luciano Burgazzi & Enrico Zio, 2021. "Reliability Assessment of Passive Safety Systems for Nuclear Energy Applications: State-of-the-Art and Open Issues," Energies, MDPI, vol. 14(15), pages 1-17, August.
    3. Olatubosun, Samuel Abiodun & Zhang, Zhijian, 2019. "Dependency consideration of passive system reliability by coupled stress-strength interference/functional relations of parameters approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 549-560.
    4. Zio, E. & Pedroni, N., 2010. "An optimized Line Sampling method for the estimation of the failure probability of nuclear passive systems," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1300-1313.

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