Skip to main content
Log in

Application of saddlepoint approximation in reliability analysis of dynamic systems

  • Published:
Earthquake Engineering and Engineering Vibration Aims and scope Submit manuscript

Abstract

The application of the saddlepoint approximation to reliability analysis of dynamic systems is investigated. The failure event in reliability problems is formulated as the exceedance of a single performance variable over a prescribed threshold level. The saddlepoint approximation technique provides a choice to estimate the cumulative distribution function (CDF) of the performance variable. The failure probability is obtained as the value of the complement CDF at a specified threshold. The method requires computing the saddlepoint from a simple algebraic equation that depends on the cumulant generating function (CGF) of the performance variable. A method for calculating the saddlepoint using random samples of the performance variable is presented. The applicable region of the saddlepoint approximation is discussed in detail. A 10-story shear building model with white noise excitation illustrates the accuracy and efficiency of the proposed methodology.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ang GL, Ang AHS and Tang WH (1992), “Optimal Importance Sampling Density Estimator,” Journal of Engineering Mechanics, 118(6): 1146–1163.

    Article  Google Scholar 

  • Au SK and Beck JL (1999), “A New Adaptive Importance Sampling Scheme,” Structural Safety, 21: 135–158.

    Article  Google Scholar 

  • Au SK and Beck JL (2001), “First Excursion Probability for Linear Systems by Very Efficient Importance Sampling,” Probabilistic Engineering Mechanics, 16(3): 193–207.

    Article  Google Scholar 

  • Au SK and Beck JL (2002), “Importance Sampling in High Dimensions,” Structural Safety, 25(2): 139–163.

    Article  Google Scholar 

  • Au SK, Papadimitriou C and Beck JL (1999), “Reliability of Uncertain Dynamical Systems with Multiple Design Points,” Structural Safety, 21: 113–133.

    Article  Google Scholar 

  • Bucher CG (1988), “Adaptive Sampling — An Iterative Fast Monte Carlo Procedure,” Structural Safety, 5: 119–126.

    Article  Google Scholar 

  • Butler RW (2007), Saddlepoint Approximations with Applications, Cambridge: Cambridge University Press.

    Google Scholar 

  • Butler RW and Wood ATA (2004), “Saddlepoint Approximation for Moment Generating Functions of Truncated Random Variables,” Annals of Statistics, 32: 2712–2730.

    Article  Google Scholar 

  • Daniels HE (1954), “Saddlepoint Approximations in Statistics,” Annals of Mathematical Statistics, 25: 631–650.

    Article  Google Scholar 

  • Daniels HE (1987), “Tail Probability Approximations,” International Statistical Review, 55: 37–48.

    Article  Google Scholar 

  • Der Kiureghian A and Dakessian T (1998), “Multiple Design Points in First and Second-order Reliability,” Structural Safety, 20: 37–49.

    Article  Google Scholar 

  • Dressel PL (1940), “Statistical Semi-invariants and Their Estimates with Particular Emphasis on Their Relation to Algebraic Invariants,” The Annals of Mathematical Statistics, 11(1): 33–57.

    Article  Google Scholar 

  • Fisher RA (1928), “Moments and Product Moments of Sampling Distributions,” Proceedings of the London Mathematical Society, 2(30): 199–238.

    Google Scholar 

  • Fishman GS (1996), Monte Carlo: Concepts, Algorithms and Applications, New York: Springer.

    Google Scholar 

  • Gatto R and Ronchetti E (1996), “General Saddlepoint Approximations of Marginal Densities and Tail Probabilities,” Journal of the American Statistical Association, 91(433): 666–673.

    Article  Google Scholar 

  • Goutis C and Casella G (1999), “Explaining the Saddlepoint Approximation,” American Statistician, 53(3): 216–224.

    Article  Google Scholar 

  • Hammersley JM and Handscomb DC (1964), Monte-Carlo Methods, London: Methuen.

    Google Scholar 

  • Hohenbichler M and Rackwitz R (1988), “Improvement of Second-order Reliability Estimates by Importance Sampling,” Journal of Engineering Mechanics, 114(12): 2195–2198.

    Article  Google Scholar 

  • Huang B and Du X (2006), “Uncertainty Analysis by Dimension Reduction Integration and Saddlepoint Approximations,” ASME Journal of Mechanical Design, 128(1): 26–33.

    Article  Google Scholar 

  • Huang B, Du X and Lakshminarayana R (2006), “A Saddlepoint Approximation based Simulation Method for Uncertainty Analysis,” International Journal of Reliability and Safety, 1(1/2): 206–224.

    Article  Google Scholar 

  • Huzurbazar S (1999), “Practical Saddlepoint Approximations,” American Statistician, 53(3): 225–232.

    Article  Google Scholar 

  • Jensen JL (1995), Saddlepoint Approximations, Oxford, Clarendon Press.

    Google Scholar 

  • Karamchandani A, Bjerager P and Cornell CA (1989), “Adaptive Importance Sampling,” Proceedings of the 5th ICOSSAR, San Francisco, pp. 855–862.

  • Lugannani R and Rice SO (1980), “Saddlpoint Approximation for the Distribution of the Sum of Independent Random Variables,” Advances in Applied Probability, 12: 475–490.

    Article  Google Scholar 

  • Melchers RE (1989), “Importance Sampling in Structural Systems,” Structural Safety, 6: 3–10.

    Article  Google Scholar 

  • Mood AM, Graybill FA and Boes DC (1974), Introduction to the Theory of Statistics, 3rd ed, New York, McGraw Hill.

    Google Scholar 

  • Papadimitrious C, Beck JL, and Katafygiotis LS (1997), “Asymptotic Expansions for Reliabilities and Moments of Uncertain Dynamic Systems,” Journal of Engineering Mechanics, 123(12): 1219–1229.

    Article  Google Scholar 

  • Reid N (1988), “Saddlepoint Methods and Statistical Inference,” Statistical Science, 3: 213–227.

    Article  Google Scholar 

  • Robinstein RY (1981), Simulation and the Monte-Carlo Method, New York: Wiley.

    Google Scholar 

  • Schuëller GI and Stix RA (1987), “A Critical Appraisal of Methods to Determine Failure Probabilities,” Structural Safety, 4: 293–309.

    Article  Google Scholar 

  • Sudjianto A, Du X and Chen W (2005), “Probabilistic Sensitivity Analysis in Engineering Design Using Uniform Sampling and Saddlepoint Approximation,” SAE 2005 Transactions Journal of Passenger Cars: Mechanical Systems, Paper No. 2005-01-0344.

  • Yuen KV and Katafygiotis LS (2005), “An Efficient Simulation Method for Reliability Analysis Using Simple Additive Rules of Probability,” Probabilistic Engineering Mechanics, 20(1): 109–114.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

Supported by: Research Committee of University of Macau Under Grant No. G074/05-06S/YKV/FST UMAC.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yuen, KV., Wang, J. & Au, SK. Application of saddlepoint approximation in reliability analysis of dynamic systems. Earthq. Eng. Eng. Vib. 6, 391–400 (2007). https://doi.org/10.1007/s11803-007-0773-8

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11803-007-0773-8

Keywords

Navigation