System Reliability and Risk Analysis

Chapter
Part of the Springer Series in Reliability Engineering book series (RELIABILITY)

Keywords

Epistemic Uncertainty Aleatory Uncertainty Fault Tree Analysis Fault Tree Analysis Accident Scenario 
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.
    Zio, E. (2009). Reliability engineering: Old problems and new challenges. Reliability Engineering and System Safety, 94, 125–141.CrossRefGoogle Scholar
  2. 2.
    Coleridge, S. T. (1983). Biographia Literaria. In J. Engell & W. J. Bate (Eds.), The collected works of Samuel Taylor Coleridge. New Jersey: Princeton University Press.Google Scholar
  3. 3.
    Saleh, J. H., & Marais, K. (2006). Highlights from the early (and Pre-) history of reliability engineering. Reliability Engineering and System Safety, 91, 249–256.CrossRefGoogle Scholar
  4. 4.
    Apostol, T. M. (1969). Calculus (2nd ed., Vol. 2). New York: Wiley.MATHGoogle Scholar
  5. 5.
    Coppola, A. (1984). Reliability Engineering of electronic Equipment: an Historical Perspective. IEEE Transactions on Reliability R-33 (1), 29–35.Google Scholar
  6. 6.
    Raymond Knight, C. (1991). Four decades of reliability progress. In Proceedings of the Annual Reliability and Maintainability Symposium, IEEE 1991, (pp. 156–160).Google Scholar
  7. 7.
    Denson, W. (1998). The History of Reliability Prediction. IEEE Transactions on Reliability, 47(2-SP), 321–328.Google Scholar
  8. 8.
    Barlow, R. E., & Proschan, F. (1975). Statistical theory of reliability and life testing. Rinehart and Winston: Holt.MATHGoogle Scholar
  9. 9.
    NRC (1975) Reactor Safety Study, an Assessment of Accident Risks, WASH-1400, Report NUREG-75/014. Washington, D.C., US Nuclear Regulatory Commission.Google Scholar
  10. 10.
    Moranda, P.B. (1975) Prediction of software reliability during debugging. In Proceedings of AnnuaL Reliability and Maintainability Symposium (pp. 327–332).Google Scholar
  11. 11.
    Cai, K. Y. (1996). System failure engineering and fuzzy methodology. An Introductory Overview, Fuzzy Sets and Systems, 83, 113–133.CrossRefGoogle Scholar
  12. 12.
    Aven, T., Jensen, U. (1999). Stochastic models in reliability. Heidelberg: Springer.Google Scholar
  13. 13.
    Aven, T., & Zio, E. (2011). Some considerations on the treatment of uncertainties in risk assessment for practical decision making. Reliability Engineering and System Safety, 96, 64–74.CrossRefGoogle Scholar
  14. 14.
    Apostolakis, G.E. (2006, 29–30 November). PRA/QRA: An historical perspective. In 2006 Probabilistic/Quantitative Risk Assessment Workshop, Taiwan.Google Scholar
  15. 15.
    Farmer, F.R. (1964). The growth of reactor safety criteria in the United Kingdom, In Anglo-Spanish Power Symposium, Madrid.Google Scholar
  16. 16.
    Garrick, B.J., & Gekler, W.C. (1967). Reliability analysis of nuclear power plant protective systems, US Atomic Energy Commission, HN-190.Google Scholar
  17. 17.
    Breeding, R. J., Helton, J. C., Gorham, E. D., & Harper, F. T. (1992). Summary description of the methods used in the probabilistic risk assessments for NUREG-1150. Nuclear Engineering and Design, 135(1), 1–27.CrossRefGoogle Scholar
  18. 18.
    NASA (2002). Probabilistic Risk Assessment Procedures Guide for NASA Managers and Practitioners.Google Scholar
  19. 19.
    Aven, T. (2003) Foundations of risk analysis, New Jersey: Wiley.Google Scholar
  20. 20.
    Bedford, T., Cooke, R. (2001). Probabilistic risk analysis, Cambridge: Cambridge University Press.Google Scholar
  21. 21.
    Henley, E. J., & Kumamoto, H. (1992). Probabilistic risk assessment. NY: IEEE Press.Google Scholar
  22. 22.
    Kaplan, S., & Garrick, B. J. (1981). On the quantitative definition of risk. Risk Analysis, 1, 1–11.CrossRefGoogle Scholar
  23. 23.
    McCormick, N. J. (1981). Reliability and risk analysis. New York: Academic Press.Google Scholar
  24. 24.
    PRA (1983, January). Procedures guide (Vols. 1&2). NUREG/CR-2300.Google Scholar
  25. 25.
    Mohaghegh, Z., Kazemi, R., & Mosleh, A. (2009). Incorporating organizational factors into probabilistic risk assessment (PRA) of complex socio-technical systems: A hybrid technique formalization. Reliability Engineering and System Safety, 94, 1000–1018.CrossRefGoogle Scholar
  26. 26.
    Parry, G., & Winter, P. W. (1981). Characterization and evaluation of uncertainty in probabilistic risk analysis. Nuclear Safety, 22(1), 28–42.Google Scholar
  27. 27.
    Apostolakis, G.E. (1990). The concept of probability in safety assessments of technological systems. Science, 250, 1359–1364.Google Scholar
  28. 28.
    Hoffman, F. O., & Hammonds, J. S. (1994). Propagation of uncertainty in risk assessments: the need to distinguish between uncertainty due to lack of knowledge and uncertainty due to variability. Risk Analysis, 14(5), 707–712.CrossRefGoogle Scholar
  29. 29.
    Helton, J.C. (2004) Alternative representations of epistemic uncertainty, Special Issue of Reliability Engineering and System Safety, 85, 1–369.Google Scholar
  30. 30.
    Helton, J. C., Johnson, J. D., Sallaberry, C. J., & Storlie, C. B. (2006). Survey of sampling-based methods for uncertainty and sensitivity analysis. Reliability Engineering & System Safety, 91, 1175–1209.CrossRefGoogle Scholar
  31. 31.
    Cacuci, D. G., & Ionescu-Bujor, M. A. (2004). Comparative review of sensitivity and uncertainty analysis of large-scale systems–II: statistical methods. Nuclear Science and Engineering, 147(3), 204–217.Google Scholar
  32. 32.
    Nilsen, T., & Aven, T. (2003). Models and model uncertainty in the context of risk analysis. Reliability Engineering & Systems Safety, 79, 309–317.CrossRefGoogle Scholar
  33. 33.
    Devooght, J. (1998). Model uncertainty and model inaccuracy. Reliability Engineering & System Safety, 59, 171–185.CrossRefGoogle Scholar
  34. 34.
    Zio, E., & Apostolakis, G. E. (1996). Two methods for the structured assessment of model uncertainty by experts in performance assessments of radioactive waste repositories. Reliability Engineering & System Safety, 54, 225–241.CrossRefGoogle Scholar
  35. 35.
    Parry, G., Drouin, M.T. (2009). Risk-Informed Regulatory Decision-Making at the U.S. NRC: Dealing with model uncertainty, Nuclear Regulatory Commission, 2009.Google Scholar
  36. 36.
    Aven, T. (2010). Some reflections on uncertainty analysis and management. Reliability Engineering & System Safety, 95, 195–201.CrossRefGoogle Scholar
  37. 37.
    de Finetti, B. (1930). Fondamenti logici del ragionamento probabilistico. Bollettino dell’Unione Matematica Italiana, 9, 258–261.MATHGoogle Scholar
  38. 38.
    Bernardo, J. M., & Smith, A. F. M. (1994). Bayesian theory. Chichester: Wiley.MATHCrossRefGoogle Scholar
  39. 39.
    Paté-Cornell, M. E. (1996). Uncertainties in risk analysis: Six levels of treatment. Reliability Engineering & System Safety, 54(2–3), 95–111.CrossRefGoogle Scholar
  40. 40.
    Baudrit, C., Dubois, D., & Guyonnet, D. (2006). Joint propagation of probabilistic and possibilistic information in risk assessment. IEEE Transactions on Fuzzy Systems, 14, 593–608.CrossRefGoogle Scholar
  41. 41.
    Baraldi, P., & Zio, E. (2008). A combined Monte Carlo and possibilistic approach to uncertainty propagation in event tree analysis. Risk Analysis, 28(5), 1309–1325.CrossRefGoogle Scholar
  42. 42.
    Flage, R., Baraldi, P., Ameruso, F., Zio, E. & Aven, T. (2009, September 7–10) Handling epistemic uncertainties in fault tree analysis by probabilistic and possibilistic approaches. In R.Bris, C. Guedes Soares & S. Martorell (Eds.), Reliability, risk and safety: theory and applications. Supplement Proceedings of the European Safety and Reliability Conference 2009 (ESREL 2009) (pp. 1761–1768). Prague: CRC Press London.Google Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.Laboratoire Génie IndustrielEcole Centrale ParisChatenay-MalabryFrance

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