Deterministic fracture mechanics analysis often involves computing critical crack size or remaining life of a component subjected to cyclic or steady state stresses.
Since many of the inputs needed to carry out the analysis have considerable scatter, conservative bounds are employed to estimate the critical crack size or the remaining life. The final results that are obtained using such methods may be overly conservative.
Probabilistic Fracture Mechanics (PFM) overcomes this difficulty by considering the variables with scatter as distributed random variables. Rather than pass/fail, it provides the probability of certain events occurring; for example, the probability of the critical crack size being reached. Monte Carlo simulation is the most commonly used technique for computing the probabilities.
In this webinar, the basic principles of PFM will be reviewed with examples from beyond-PRAISE, a Probabilistic Fracture Mechanics software for computing probabilities of leaks and breaks in nuclear power plant cooling piping subjected to fatigue, PWSCC and FAC.