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By combining detailed mathematical modeling of the physics involved in NDE with a broader and robust engineering approach based on the sequential steps of screening, modeling and optimization, it is possible to generate metamodels that can support NDE engineering efforts to evaluate the applicability of NDE in a wider context, as a complement to the repeatability, reproducibility and capability studies normally performed. The aim of the initial screening phase is to effectively evaluate and prioritize NDE control parameters from a wider perspective regarding the demands of a specific application and to prioritize parameters of lesser importance for the outcome on the basis of economic and practical considerations. The aim of the second and third steps is to study the influence of the important parameters and to perform sensitivity analyses of reproducibility and repeatability, for example, followed by procedure development, respectively. The methodology is straightforward when it comes to smooth response surfaces of lower order (up to second or third order). Generally, the recommendation for the screening phase is ‘to be bold’ for the definition of the experimental range for each parameter – meaning to make them as wide as possibly relevant for the specific application. For NDE applications not following the Berens assumption for POD studies, e.g., large cracks yield large response signals, such as the varying signal amplitudes from surface breaking notches in ultrasonic testing, the mentioned recommendation of ‘be-bold’ screening phase may lead to incorrect prioritization of parameters. In this publication, this is illustrated by how the width of the experimental range for the control parameters tested during screening actually influences the screening results. Two basic ultrasonic testing set-ups have been compared using the SimSUNDT simulation software package: surface breaking notch (SBN) and side drilled hole (SDH). Even though the results were anticipated, they pointed out the need to further develop the screening methodology supporting NDE engineering, especially when it comes to addressing the issue of applicability. Does the data collected tell us what we actually want to know about the tested application? Or does it only tell us something about the NDE method?

The Potential in Simulation and Metamodeling for the Understanding and Development of NDE