Abstract
In the context of corrosion engineering it is often natural to be concerned with extreme events. This is because, firstly, it is these extreme events that often lead to failure and, secondly, it may only be possible to measure the extremes, with much of the underlying measurements by their very nature unobservable Statistical methods relating to extreme value theory can be used to model and predict the statistical behaviour of extremes such as the largest pit, thinnest wall, maximum penetration or similar assessment of a corrosion phenomenon. These techniques can be applied to the single largest value, or to a given number of the largest values, measured over individual areas or coupons; or to all values exceeding a given threshold. The data can be modeled to account for dependence on environmental conditions, surface area examined, and the duration of exposure or of experimentation. The application of a selection of these techniques is demonstrated on data from industry and from laboratory experiments.