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Discrete Probability Distributions for Probabilistic Fracture Mechanics

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  • Robert E. Kurth
  • David C. Cox

Abstract

Recently, discrete probability distributions (DPDs) have been suggested for use in risk analysis calculations to simplify the numerical computations which must be performed to determine failure probabilities. Specifically, DPDs have been developed to investigate probabilistic functions, that is, functions whose exact form is uncertain. The analysis of defect growth in materials by probabilistic fracture mechanics (PFM) models provides an example in which probabilistic functions play an important role. This paper compares and contrasts Monte Carlo simulation and DPDs as tools for calculating material failure due to fatigue crack growth. For the problem studied, the DPD method takes approximately one third the computation time of the Monte Carlo approach for comparable accuracy. It is concluded that the DPD method has considerable promise in low‐failure‐probability calculations of importance in risk assessment. In contrast to Monte Carlo, the computation time for the DPD approach is relatively insensitive to the magnitude of the probability being estimated.

Suggested Citation

  • Robert E. Kurth & David C. Cox, 1985. "Discrete Probability Distributions for Probabilistic Fracture Mechanics," Risk Analysis, John Wiley & Sons, vol. 5(3), pages 235-240, September.
    • Handle: RePEc:wly:riskan:v:5:y:1985:i:3:p:235-240
    DOI: 10.1111/j.1539-6924.1985.tb00175.x
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    References listed on IDEAS

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    1. Stanley Kaplan, 1981. "On The Method of Discrete Probability Distributions in Risk and Reliability Calculations–Application to Seismic Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 1(3), pages 189-196, September.
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    Cited by:

    1. Stan Kaplan & James C. Lin, 1987. "An Improved Condensation Procedure in Discrete Probability Distribution Calculations," Risk Analysis, John Wiley & Sons, vol. 7(1), pages 15-19, March.

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