IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v216y2021ics0951832021004464.html
   My bibliography  Save this article

Numerically efficient computation of the survival signature for the reliability analysis of large networks

Author

Listed:
  • Behrensdorf, Jasper
  • Regenhardt, Tobias-Emanuel
  • Broggi, Matteo
  • Beer, Michael

Abstract

Societal growth thrives on the performance of critical infrastructure systems such as water supply systems, transportation networks or electrical distribution systems. This makes the reliability analysis of these systems a core focus for researchers today. The survival signature is a novel tool for analysing complex networks efficiently and outperforms traditional techniques in several key factors. Its most unique feature being a full separation of the system structure from probabilistic information. This in turn allows for the consideration of diverse component failure descriptions such as dependencies, common causes of failure and imprecise probabilities. However, the numerical effort to compute the survival signature increases with network size and prevents analysis of complex systems. This work presents a new method to approximate the survival signature, where system configurations of low interest are first excluded using percolation theory, while the remaining parts of the signature are approximated by Monte Carlo simulation. The approach is able to accurately approximate the survival signature with very small error at a massive reduction in computational demands. The accuracy and performance are highlighted using several simple test systems as well as two real world problems.

Suggested Citation

  • Behrensdorf, Jasper & Regenhardt, Tobias-Emanuel & Broggi, Matteo & Beer, Michael, 2021. "Numerically efficient computation of the survival signature for the reliability analysis of large networks," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
  • Handle: RePEc:eee:reensy:v:216:y:2021:i:c:s0951832021004464
    DOI: 10.1016/j.ress.2021.107935
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832021004464
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2021.107935?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Patelli, Edoardo & Feng, Geng & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2017. "Simulation methods for system reliability using the survival signature," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 327-337.
    2. Huang, Xianzhen & Aslett, Louis J.M. & Coolen, Frank P.A., 2019. "Reliability analysis of general phased mission systems with a new survival signature," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 416-422.
    3. Hindolo George-Williams & Geng Feng & Frank PA Coolen & Michael Beer & Edoardo Patelli, 2019. "Extending the survival signature paradigm to complex systems with non-repairable dependent failures," Journal of Risk and Reliability, , vol. 233(4), pages 505-519, August.
    4. Reed, Sean, 2017. "An efficient algorithm for exact computation of system and survival signatures using binary decision diagrams," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 257-267.
    5. Serkan Eryilmaz & Altan Tuncel, 2016. "Generalizing the survival signature to unrepairable homogeneous multi‐state systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(8), pages 593-599, December.
    6. Enrico Zio, 2013. "System Reliability and Risk Analysis," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 7-17, Springer.
    7. Feng, Geng & Patelli, Edoardo & Beer, Michael & Coolen, Frank P.A., 2016. "Imprecise system reliability and component importance based on survival signature," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 116-125.
    8. Enrico Zio, 2013. "Monte Carlo Simulation: The Method," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 19-58, Springer.
    9. Li, Yao & Coolen, Frank P.A. & Zhu, Caichao & Tan, Jianjun, 2020. "Reliability assessment of the hydraulic system of wind turbines based on load-sharing using survival signature," Renewable Energy, Elsevier, vol. 153(C), pages 766-776.
    10. Enrico Zio, 2013. "The Monte Carlo Simulation Method for System Reliability and Risk Analysis," Springer Series in Reliability Engineering, Springer, edition 127, number 978-1-4471-4588-2, September.
    11. Nan, Cen & Sansavini, Giovanni, 2017. "A quantitative method for assessing resilience of interdependent infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 35-53.
    12. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    13. Aesha Najem & Frank P. A. Coolen, 2019. "System reliability and component importance when components can be swapped upon failure," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(3), pages 399-413, May.
    14. Enrico Zio, 2013. "System Reliability and Risk Analysis by Monte Carlo Simulation," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 59-81, Springer.
    15. Li, Daqing & Zhang, Qiong & Zio, Enrico & Havlin, Shlomo & Kang, Rui, 2015. "Network reliability analysis based on percolation theory," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 556-562.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Jiarui & Tang, Bin & Duan, Yuxian & Huang, Jian, 2023. "Percolation phase transition in the heterogeneous multi-coupled interdependent network," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    2. Du, Yi-Mu & Sun, C.P., 2022. "A novel interpretable model of bathtub hazard rate based on system hierarchy," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    3. Chang, Miaoxin & Huang, Xianzhen & Coolen, Frank PA & Coolen-Maturi, Tahani, 2023. "New reliability model for complex systems based on stochastic processes and survival signature," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1349-1364.
    4. Wang, Shaoxuan & Yao, Yuantao & Ge, Daochuan & Lin, Zhixian & Wu, Jie & Yu, Jie, 2023. "Reliability evaluation of standby redundant systems based on the survival signatures methods," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    5. Shi, Yan & Behrensdorf, Jasper & Zhou, Jiayan & Hu, Yue & Broggi, Matteo & Beer, Michael, 2024. "Network reliability analysis through survival signature and machine learning techniques," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    6. Rusnak, Patrik & Zaitseva, Elena & Levashenko, Vitaly & Bolvashenkov, Igor & Kammermann, Jörg, 2024. "Importance analysis of a system based on survival signature by structural importance measures," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    7. Monfared, M.A.S. & Rezazadeh, Masoumeh & Alipour, Zohreh, 2022. "Road networks reliability estimations and optimizations: A Bi-directional bottom-up, top-down approach," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    8. Salomon, Julian & Winnewisser, Niklas & Wei, Pengfei & Broggi, Matteo & Beer, Michael, 2021. "Efficient reliability analysis of complex systems in consideration of imprecision," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    9. Maryam Kelkinnama & Serkan Eryilmaz, 2023. "Some reliability measures and maintenance policies for a coherent system composed of different types of components," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(1), pages 57-82, January.
    10. Di Maio, Francesco & Pettorossi, Chiara & Zio, Enrico, 2023. "Entropy-driven Monte Carlo simulation method for approximating the survival signature of complex infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 231(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Salomon, Julian & Winnewisser, Niklas & Wei, Pengfei & Broggi, Matteo & Beer, Michael, 2021. "Efficient reliability analysis of complex systems in consideration of imprecision," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    2. Di Maio, Francesco & Pettorossi, Chiara & Zio, Enrico, 2023. "Entropy-driven Monte Carlo simulation method for approximating the survival signature of complex infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    3. Coolen-Maturi, Tahani & Coolen, Frank P.A. & Balakrishnan, Narayanaswamy, 2021. "The joint survival signature of coherent systems with shared components," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    4. Hashemi, M. & Asadi, M. & Zarezadeh, S., 2020. "Optimal maintenance policies for coherent systems with multi-type components," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    5. Guowang Meng & Hongle Li & Bo Wu & Guangyang Liu & Huazheng Ye & Yiming Zuo, 2023. "Prediction of the Tunnel Collapse Probability Using SVR-Based Monte Carlo Simulation: A Case Study," Sustainability, MDPI, vol. 15(9), pages 1-21, April.
    6. Michael Saidani & Alissa Kendall & Bernard Yannou & Yann Leroy & François Cluzel, 2019. "Closing the loop on platinum from catalytic converters: Contributions from material flow analysis and circularity indicators," Post-Print hal-02094798, HAL.
    7. Michele Compare & Francesco Di Maio & Enrico Zio & Fausto Carlevaro & Sara Mattafirri, 2016. "Improving scheduled maintenance by missing data reconstruction: A double-loop Monte Carlo approach," Journal of Risk and Reliability, , vol. 230(5), pages 502-511, October.
    8. Chiacchio, Ferdinando & D’Urso, Diego & Famoso, Fabio & Brusca, Sebastian & Aizpurua, Jose Ignacio & Catterson, Victoria M., 2018. "On the use of dynamic reliability for an accurate modelling of renewable power plants," Energy, Elsevier, vol. 151(C), pages 605-621.
    9. Wang, Fan & Li, Heng, 2018. "System reliability under prescribed marginals and correlations: Are we correct about the effect of correlations?," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 94-104.
    10. Tito G. Amaral & Vitor Fernão Pires & Armando Cordeiro & Daniel Foito & João F. Martins & Julia Yamnenko & Tetyana Tereschenko & Liudmyla Laikova & Ihor Fedin, 2023. "Incipient Fault Diagnosis of a Grid-Connected T-Type Multilevel Inverter Using Multilayer Perceptron and Walsh Transform," Energies, MDPI, vol. 16(6), pages 1-18, March.
    11. Zhang, Hanxiao & Sun, Muxia & Li, Yan-Fu, 2022. "Reliability–redundancy allocation problem in multi-state flow network: Minimal cut-based approximation scheme," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    12. Mi, Jinhua & Beer, Michael & Li, Yan-Feng & Broggi, Matteo & Cheng, Yuhua, 2020. "Reliability and importance analysis of uncertain system with common cause failures based on survival signature," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    13. Tosoni, E. & Salo, A. & Govaerts, J. & Zio, E., 2019. "Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 561-573.
    14. Shi, Yan & Behrensdorf, Jasper & Zhou, Jiayan & Hu, Yue & Broggi, Matteo & Beer, Michael, 2024. "Network reliability analysis through survival signature and machine learning techniques," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    15. Penttinen, Jussi-Pekka & Niemi, Arto & Gutleber, Johannes & Koskinen, Kari T. & Coatanéa, Eric & Laitinen, Jouko, 2019. "An open modelling approach for availability and reliability of systems," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 387-399.
    16. Rocco, Claudio M. & Moronta, José & Ramirez-Marquez, José E. & Barker, Kash, 2017. "Effects of multi-state links in network community detection," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 46-56.
    17. Compare, Michele & Bellani, Luca & Zio, Enrico, 2019. "Optimal allocation of prognostics and health management capabilities to improve the reliability of a power transmission network," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 164-180.
    18. Babykina, Génia & Brînzei, Nicolae & Aubry, Jean-François & Deleuze, Gilles, 2016. "Modeling and simulation of a controlled steam generator in the context of dynamic reliability using a Stochastic Hybrid Automaton," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 115-136.
    19. Compare, Michele & Bellani, Luca & Zio, Enrico, 2017. "Reliability model of a component equipped with PHM capabilities," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 4-11.
    20. Gascard, Eric & Simeu-Abazi, Zineb, 2018. "Quantitative Analysis of Dynamic Fault Trees by means of Monte Carlo Simulations: Event-Driven Simulation Approach," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 487-504.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:216:y:2021:i:c:s0951832021004464. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.