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.
Dr. Dedhia’s areas of expertise include fracture mechanics, both deterministic and probabilistic, statistical data analysis, development of engineering software and providing training. Since joining SI in 2007, Dr. Dedhia has been involved in fracture mechanics analysis and the development of pc-CRACK software. His current work includes the development of beyond-PRAISE, a PFM software for nuclear piping. He is also a key contributor to the NRC-EPRI xLPR project. Dr. Dedhia has developed statistically based inspection plans, databases for pressure vessel fracture toughness data and statistical methodology for large volumeMore...