Abstract
The probability of detection curve is a standard tool in several industries to evaluate the performance of non destructive testing (NDT) procedures for the detection of harmful defects for the inspected structure. Due to new capabilities of NDT process numerical simulation, model assisted probability of detection (MAPOD) approaches have also been recently developed. In this paper, a generic and progressive MAPOD methodology is proposed. Limits and assumptions of the classical methods are enlightened, while new metamodel-based methods are proposed. They allow to access to relevant information based on sensitivity analysis of MAPOD inputs. Applications are performed on eddy current non destructive examination numerical data.
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Acknowledgements
Part of this work has been backed by French National Research Agency (ANR) through project ByPASS ANR-13-MONU-0011. All the calculations were performed by using the OpenTURNS software [2]. We are grateful to Léa Maurice for initial works on this subject, as Pierre-Emile Lhuillier, Pierre Thomas, François Billy, Pierre Calmon, Vincent Feuillard and Nabil Rachdi for helpful discussions. Thanks to Dominique Thai-Van who provided a first version of Fig. 14.
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Le Gratiet, L., Iooss, B., Blatman, G. et al. Model Assisted Probability of Detection Curves: New Statistical Tools and Progressive Methodology. J Nondestruct Eval 36, 8 (2017). https://doi.org/10.1007/s10921-016-0387-z
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DOI: https://doi.org/10.1007/s10921-016-0387-z