Using Modeling and Metamodels for Reliability Study in Non-Destructive Evaluation

Abstract

As in any other measurement process, NDE is subject to variability whose impact can be assessed to guarantee a given level of performance. Once NDE prevents catastrophic failures, deaths and environmental damage, identifying uncertainties and variability in NDE help to design more reliable inspections, therefore is a process that saves lives. This is the goal of a reliability study. Statistical indicators such as Probability of Detection (POD) curves give insights to allow building of mechanical designs with enough « secure margin » for structural integrity and to also define appropriate maintenance & inspection cycles. Simulation is very useful to support performance or reliability demonstrations that require a lot of data (such as POD studies and qualification campaigns), and where simulation can help by reducing the number of necessary mock-ups and experimental trials. In addition to physical models, the NDE simulation software CIVA now offers meta-modelling techniques. Built from an initial set of physical simulations, such surrogate models give the user the possibility to generate a massive amount of data while combining and exploring multi parametric variations. This is particularly efficient in the context of reliability studies, when you have to find the best settings, track the worst-case scenario or build POD curves. This paper illustrates the use of this meta-modelling approach for the reliability study of a longitudinal weld AUT inspection. Real pipe mill inspection data are provided and compared to modelling and meta-modelling results.