Probabilistic modeling and sizing of embedded flaws in ultrasonic non-destructive inspections for fatigue damage prognostics and structural integrity assessment

Abstract

The paper presents a systematic method and procedure for probabilistic fatigue life prediction using non-destructive testing data under uncertainty. The procedure is developed using uncertainty quantification models for detection, sizing, fatigue model parameters and inputs. The probability of detection model is based on a classical log-linear model coupling the actual flaw size with the NDE reported size. Using probabilistic modeling and Bayes theorem, the distribution of the actual flaw size is derived for both NDE data without flaw indications and NDE data with flaw indications. Fatigue damage and structural integrity assessment are suggested based on the developed method and procedure. A turbine rotor example with realistic NDE inspection data is presented to demonstrate the overall methodology. Calculation and interpretation of the results based on risk recommendations for industrial applications are given. The influence of the NDE detection threshold to the assessment results, and error analysis of the assessment results are discussed in detail.