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Extreme value analysis (EVA) is a statistical tool to estimate the likelihood of the occurrence of extreme values based on a few basic assumptions and observed/measured data. While output of this type of analysis cannot ever rival a full inspection, it can be a useful tool for partial coverage inspection (PCI), where access, cost or other limitations result in an incomplete dataset. In PCI, EVA can be used to estimate the largest defect that can be expected. Commonly the return level method is used to do this. However, the uncertainties associated with the return level are less commonly reported on. This paper presents an overview of how the return level and its 95% confidence intervals can be determined and how they vary based on different analysis parameters, such as the block size and extrapolation ratio. The analysis is then tested on simulated wall thickness data that has Gaussian and Exponential distributions. A curve that presents the confidence interval width as a percentage of the actual return level and as a function of the extrapolation ratio is presented. This is valid for the particular scale parameter (σ ) that was associated with the simulated data. And for this data it was concluded that, in general, extrapolations to an area the size of 500–1000 times the inspected area result in acceptable return level uncertainties ( |
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