Abstract: A method and software system for flaw identification, grouping and sizing for fatigue life assessment for rotors used in turbines and generators. The method includes providing ultrasonic data of a plurality of rotor slices and providing volume reconstruction of the ultrasonic data. The method also includes providing in-slice identification, grouping and sizing of flaw indications in the rotor based on the volume reconstruction. Further, the method includes providing inter-slice identification, grouping and sizing of the flaw indications based on the in-slice flaw indications and providing flaw location and size information. The method can be used in both phased-array and A-scan inspections.

Abstract: A method for probabilistic fatigue life prediction using nondestructive testing data considering uncertainties from nondestructive examination (NDE) data and fatigue model parameters. The method utilizes uncertainty quantification models for detection, sizing, fatigue model parameters and inputs. A probability of detection model is developed based on a log-linear model coupling an actual flaw size with a nondestructive examination (NDE) reported size. A distribution of the actual flaw size is derived for both NDE data without flaw indications and NDE data with flaw indications by using probabilistic modeling and Bayes theorem. A turbine rotor example with real world NDE inspection data is presented to demonstrate the overall methodology.

Abstract: A method of fatigue life prediction including: calculating a critical crack size of an object of interest; identifying a first flaw in ultrasound data of the object of interest; determining that the first flaw interacts with a second flaw, the first flaw is to be merged with the second flaw, or the first flaw is isolated; calculating an initial crack size based on the determination; and calculating an increase in the initial crack size due to fatigue and creep to determine a number of load cycles until the initial crack size reaches the critical crack size.

Abstract: A method for probabilistic fatigue life prediction using nondestructive testing data considering uncertainties from nondestructive examination (NDE) data and fatigue model parameters. The method utilizes uncertainty quantification models for detection, sizing, fatigue model parameters and inputs. A probability of detection model is developed based on a log-linear model coupling an actual flaw size with a nondestructive examination (NDE) reported size. A distribution of the actual flaw size is derived for both NDE data without flaw indications and NDE data with flaw indications by using probabilistic modeling and Bayes theorem. A turbine rotor example with real world NDE inspection data is presented to demonstrate the overall methodology.

Abstract: A method and software system for flaw identification, grouping and sizing for fatigue life assessment for rotors used in turbines and generators. The method includes providing ultrasonic data of a plurality of rotor slices and providing volume reconstruction of the ultrasonic data. The method also includes providing in-slice identification, grouping and sizing of flaw indications in the rotor based on the volume reconstruction. Further, the method includes providing inter-slice identification, grouping and sizing of the flaw indications based on the in-slice flaw indications and providing flaw location and size information. The method can be used in both phased-array and A-scan inspections.

Abstract: A method of fatigue life prediction including: calculating a critical crack size of an object of interest; identifying a first flaw in ultrasound data of the object of interest; determining that the first flaw interacts with a second flaw, the first flaw is to be merged with the second flaw, or the first flaw is isolated; calculating an initial crack size based on the determination; and calculating an increase in the initial crack size due to fatigue and creep to determine a number of load cycles until the initial crack size reaches the critical crack size.