A methodology for predicting probability of detection for ultrasonic testing

Theoretical models of physical processes have been utilized to predict expected flaw response and probability of detection (POD). The models have as inputs the most important inspection-related variables and also account for some sources of variability (e.g., material noise and scan plan). These models, however, do not adequately describe all sources of variability (e.g., human factors deliberate or unavoidable changes in inspection system properties, or complex changes in flaw morphology). This paper describes a new methodology that combines the use of physical modeling of factors that can be modeled adequately and statistical modeling of limited NDE inspection data (e.g. a-hat versus a data) to account for other important factors that are not included in the physical model. The resulting physical/statistical model provides predictions of POD or other inspection-evaluation metrics as a function of specified inspection plans and Raw characteristics that extend the range of predictions that could be made empirically, based on the available data. We illustrate the methodology with example data from experiments on synthetic hard-alpha flaws.