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Potential Applications of Discrete-event Simulation and Fuzzy Rule-based Systems to Structural Reliability and Availability

  • Angel A. Juan
  • Albert Ferrer
  • Carles Serrat
  • Javier Faulin
  • Gleb Beliakov
  • Joshua Hester
Chapter
  • 1.7k Downloads
Part of the Springer Series in Reliability Engineering book series (RELIABILITY)

Abstract

This chapter discusses and illustrates some potential applications of discrete-event simulation (DES) techniques in structural reliability and availability analysis, emphasizing the convenience of using probabilistic approaches in modern building and civil engineering practices. After reviewing existing literature on the topic, some advantages of probabilistic techniques over analytical ones are highlighted. Then, we introduce a general framework for performing structural reliability and availability analysis through DES. Our methodology proposes the use of statistical distributions and techniques – such as survival analysis – to model component-level reliability. Then, using failure- and repair-time distributions and information about the structural logical topology (which allows determination of the structural state from their components’ state), structural reliability, and availability information can be inferred. Two numerical examples illustrate some potential applications of the proposed methodology to achieving more reliable and structural designs. Finally, an alternative approach to model uncertainty at component level is also introduced as ongoing work. This new approach is based on the use of fuzzy rule-based systems and it allows the introduction of experts’ opinions and evaluations in our methodology.

Keywords

Wind Turbine Failure Probability Structural Failure Structural Reliability Minimal Path 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Beliakov G, Pradera A, Calvo T (2007) Aggregation functions: a guide for practitioners. In: Studies in fuzziness and soft computing, Vol 221. Springer, BerlinGoogle Scholar
  2. 2.
    Billinton R, Wang P (1999) Teaching distribution systems reliability evaluation using Monte Carlo simulation. IEEE Trans Power Syst 14:397–403CrossRefGoogle Scholar
  3. 3.
    Camarinopoulos L, Chatzoulis A, Frondistou-Yannas M, Kallidromitis V (1999) Assessment of the time-dependent structural reliability of buried water mains. Reliab Eng Syst Saf 65(1):41–53CrossRefGoogle Scholar
  4. 4.
    Coit D (2000) System reliability prediction prioritization strategy. In: 2000 proceedings annual reliability and maintainability symposium, Los Angeles, CA. IEEE, Los Alamitos, CA, USA, pp 175–180Google Scholar
  5. 5.
    Ditlevsen O, Madsen H (2007) Structural reliability methods. John Wiley, Chichester, UK. Available at http://www.web.mek.dtu.dk/staff/od/books.htm Google Scholar
  6. 6.
    Fagan T, Wilson M (1968) Monte Carlo simulation of system reliability. In: Proceedings of the 23rd ACM national conference. ACM, New York, NY, USA, pp 289–293CrossRefGoogle Scholar
  7. 7.
    Faulin J, Juan A, Serrat C, Bargueño V (2007) Using simulation to determine reliability and availability of telecommunication networks. Eur J Ind Eng 1(2):131–151CrossRefGoogle Scholar
  8. 8.
    Faulin J, Juan A, Serrat C, Bargueño V (2008) Improving availability of time-dependent complex systems by using the SAEDES simulation algorithms. Reliab Eng Syst Saf 93(11):1761–1771CrossRefGoogle Scholar
  9. 9.
    Frangopol D, Maute K (2003) Life-cycle reliability-based optimization of civil and aerospace structures. Comput Struct 81(7):397–410CrossRefGoogle Scholar
  10. 10.
    Juan A, Faulin J, Serrat C, Sorroche M, Ferrer A (2008) A simulation-based algorithm to predict time-dependent structural reliability. In: Rabe M (ed) Advances in simulation for production and logistics applications. Fraunhofer IRB Verlag, Stuttgart, pp 555–564Google Scholar
  11. 11.
    Juan A, Faulin J, Sorroche M, Marques J (2007) J-SAEDES: A simulation software to improve reliability and availability of computer systems and networks. In: Proceedings of the 2007 winter simulation conference, Washington DC. IEEE Press, Piscataway, NJ, USA, pp 2285–2292Google Scholar
  12. 12.
    Juan A, Vila A (2002) SREMS: System reliability using Monte Carlo simulation with VBA and Excel. Qual Eng 15(2):333–340CrossRefGoogle Scholar
  13. 13.
    Kamal H, Ayyub B (1999) Reliability assessment of structural systems using discrete-event simulation. In: 13th ASCE Engineering Mechanics Division specialty conference, Baltimore, MD. Available at http://citeseer.ist.psu.edu/cache/papers/cs/13123/http:zSzzSzrongo.ce.jhu.eduzSzemd99zSsessionszSzpaperszSzkamal1.pdf/reliability-assessment-of-structural.pdf
  14. 14.
    Kawamura K, Miyamoto A (2003) Condition state evaluation of existing reinforced concrete bridges using neuro-fuzzy hybrid system. Comput Struct 81:1931–1940CrossRefGoogle Scholar
  15. 15.
    Laumakis P, Harlow G (2002) Structural reliability and Monte Carlo simulation. Int J Math Educ Sci Technol 33(3):377–387CrossRefGoogle Scholar
  16. 16.
    Law A (2007) Simulation modeling and analysis. McGraw-Hill, New York, NY, USAGoogle Scholar
  17. 17.
    Lertwongkornkit P, Chung H, Manuel L (2001) The use of computer applications for teaching structural reliability. In: Proceedings of the 2001 ASEE Gulf-Southwest Section annual conference, Austin, TX. Available at http://www.ce.utexas.edu/prof/Manuel/Papers/asee2001.PDF
  18. 18.
    Li C (1995) Computation of the failure probability of deteriorating structural systems. Comput Struct 56(6):1073–1079zbMATHCrossRefGoogle Scholar
  19. 19.
    Mahadevan S, Raghothamachar P (2000) Adaptive simulation for system reliability analysis of large structures. Comput Struct 77:725–734CrossRefGoogle Scholar
  20. 20.
    Marek P, Gustar M, Anagnos T (1996) Simulation based reliability assessment for structural engineers. CRC Press, Boca Raton, FLGoogle Scholar
  21. 21.
    Marquez A, Sanchez A, Iung B (2005) Monte Carlo-based assessment of system availability. a case study for co-generation plants. Reliab Eng Syst Saf 88(3):273–289CrossRefGoogle Scholar
  22. 22.
    Meeker W, Escobar L (1998) Statistical methods for reliability data. John Wiley & Sons, New York, NY, USAzbMATHGoogle Scholar
  23. 23.
    Melchers R (1999) Structural reliability: analysis and prediction. John Wiley & Sons, Chichester, UKGoogle Scholar
  24. 24.
    Nilson A, Darwin D, Dolan C (2003) Design of concrete structures. McGraw-Hill Science, New York, NY, USAGoogle Scholar
  25. 25.
    Park S, Choi S, Sikorsky C, Stubbs N (2004) Efficient method for calculation of system reliability of a complex structure. Int J Solid Struct 41:5035–5050zbMATHCrossRefGoogle Scholar
  26. 26.
    Petryna Y, Krätzig W (2005) Computational framework for long-term reliability analysis of RC structures. Comput Meth Appl Mech Eng 194(12-16):1619–1639zbMATHCrossRefGoogle Scholar
  27. 27.
    Piegat A (2005) A new definition of the fuzzy set. Int J Appl Math Comput Sci 15(1):125–140zbMATHMathSciNetGoogle Scholar
  28. 28.
    Song J, Kang W (2009) System reliability and sensitivity under statistical dependence by matrix-based system reliability method. Struct Saf 31(2):148–156CrossRefMathSciNetGoogle Scholar
  29. 29.
    Stewart M, Rosowsky D (1998) Time-dependent reliability of deteriorating reinforced concrete bridge decks. Struct Saf 20:91–109CrossRefGoogle Scholar
  30. 30.
    Thoft-Christensen P, Murotsu Y (1986) Application of structural systems reliability theory. Springer, New York, NY, USAzbMATHGoogle Scholar
  31. 31.
    Vukazich S, Marek P (2001) Structural design using simulation based reliability assessment. Acta Polytech 41(4–5):85–92Google Scholar
  32. 32.
    Zimmerman H (1996) Fuzzy sets theory and its applications. Kluwer, Boston, MAGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  • Angel A. Juan
    • 1
  • Albert Ferrer
    • 2
  • Carles Serrat
    • 2
  • Javier Faulin
    • 3
  • Gleb Beliakov
    • 4
  • Joshua Hester
    • 1
  1. 1.Dept. of Computer Sciences, Multimedia and Telecommunication, IN3Open University of CataloniaBarcelonaSpain
  2. 2.Institute of Statistics and Mathematics Applied to the Building Construction, EPSEBTechnical University of CataloniaBarcelonaSpain
  3. 3.Dept. of Statistics and Operations ResearchPublic University of NavarrePamplonaSpain
  4. 4.School of Engineering and Information TechnologyDeakin UniversityMelbourneAustralia

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