Open Collections

Inter-relationship between physical-chemical processes and extreme value modelling

International Conference on Applications of Statistics and Probability (12th : 2015 : Vancouver, B.C.)

Of considerable interest in various industries such as aerospace is the longer term safety of aluminium alloy structures and the effect of deterioration. Corrosion of aluminium alloys occurs mainly as pitting for which uncertainty and variability issues usually have led to maximum pit depth being considered a random variable that is also a function of time. An extreme value distribution is fitted to the statistical data obtained from multiple observations. Usually, the selection of the most appropriate model is based on the claim that one or other distribution is a ‘better fit’ to the data. This classical approach takes no account of prior knowledge of the underlying physicochemical process(es) that drive pitting behaviour. A more sophisticated approach uses such prior understanding. Recently it was shown that the linear model implied by the ‘pitting rate’ is too simplistic. Instead, a bi-modal model better represents both mass-loss as a function of exposure period and the evolution of maximum pit depth with time. This leads directly the possibility that one distribution may not be suitable for the whole range of pit depth data. These concepts are illustrated with examples.

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This collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.

Vancouver : University of British Columbia Library

10.14288/1.0076183

Non UBC

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/