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Probabilistic Life Prediction as Easy as It Looks
Annis C


Pages: 12    Published: Jan 2004


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Source: STP1450-EB


Abstract
Many engineers effect probabilistic life prediction by replacing constants with probability distributions and carefully modeling the physical relationships among the parameters. Surprisingly, the relationships among the constants are often given short shrift, if not ignored altogether. Few recognize that while this simple substitution of distributions for constants will indeed produce a nondeterministic result, the corresponding probabilities are often woefully inaccurate. In fact, even the trend can be wrong, so these results can't even be used for sensitivity studies. This paper explores the familiar Paris equation relating crack growth rate and applied stress intensity to illustrate many statistical realities that are often ignored by otherwise careful engineers. Although the examples are Monte Carlo, the lessons also apply to other methods of probabilistic life prediction, including FORM/SORM (First/Second Order Reliability Method) and related fast probability integration methods.


Keywords:
life prediction, crack growth, Paris equation, probability, statistics, simulation, Monte Carlo, nondeterministic, probabilistic, joint, conditional, marginal, multivariate

Paper ID: STP11275S
Committee/Subcommittee: E08.06
DOI: 10.1520/STP11275S
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