The weibull time-dependent growth model of marine corrosion in seawater ballast tank

This paper demonstrates the application of the probability distributions in modeling the time dependent growth behaviour of corrosion pits in vessel’s seawater ballast tanks. The proposed model is capable of projecting the likely growth pattern of corrosion pits in the future by eliminating the de...

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Bibliographic Details
Main Authors: Md. Noor, Norhazilan, Smith, George H., Yahaya, Nordin
Format: Article
Language:English
English
Published: Faculty of Civil Engineering, Universiti Teknologi Malaysia 2007
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Online Access:http://eprints.utm.my/id/eprint/8449/5/NorhazilanMdNoor2007_TheWeibullTimeDependentGrowth.pdf
http://eprints.utm.my/id/eprint/8449/3/index.html
http://eprints.utm.my/id/eprint/8449/
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Summary:This paper demonstrates the application of the probability distributions in modeling the time dependent growth behaviour of corrosion pits in vessel’s seawater ballast tanks. The proposed model is capable of projecting the likely growth pattern of corrosion pits in the future by eliminating the dependent factors governing to corrosion rate such as environmental factors, properties of material and operational condition. To express appropriately the high variability of corrosion wastage which contributes to the uncertainties in corrosion assessment, the Weibull probability distributions were proposed which are able to predict the growth of corrosion pit in seawater ballast tank. It is obvious that the provided information from the vessel inspections is full of uncertainties, owing to the nature of marine corrosion as reflected by the poor correlation result of averaged depth against time. In spite of the drawback, the research is able to demonstrate the optimisation of the data purposely for corrosion growth prediction. The predicted data as compared to actual data yields results with moderate accuracy based on Root-Mean-Square-Error (RMSE), yet still promising provided that better quality data can become available in the future. The proposed probabilistic models are intended to simplify the modelling process so that the available data can be fully utilised for prediction and structural evaluation purposes.