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  4. Updatable spatio-temporal probabilistic corrosion modeling for offshore structures
 
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Updatable spatio-temporal probabilistic corrosion modeling for offshore structures

Publikationstyp
Conference Paper
Date Issued
2018-09-25
Sprache
English
Author(s)
Neumann, Karoline M.  
Vårdal, Ole Tom  
Ehlers, Sören  
Institut
Konstruktion und Festigkeit von Schiffen M-10  
TORE-URI
http://hdl.handle.net/11420/2453
First published in
Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE  
Number in series
11B
Citation
Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE (11B): V11BT12A026 (2018)
Contribution to Conference
ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2018  
Publisher DOI
10.1115/OMAE2018-78684
Scopus ID
2-s2.0-85055312260
Corrosion models are important to assess how the corrosion influences current and future structural strength. For this purpose it is desirable to describe the uneven corrosion diminution of the irregular surface (i.e. Space) and progression (i.e. Time) in various corrosive environments. Thickness measurements give an indication of the current state, and should be considered in the corrosion model. The inherit uncertainty in corrosion argues for a probabilistic type of corrosion model. Probabilistic models to describe corrosion in time and space, and that can be updated with observations exist, but are typically too complicated for practical engineering use for in-service corrosion assessment. Simpler models exist, that do not describe all of the mentioned aspects (probabilistic, updatable, describe corrosion in time, space and various environments). Here, a simple model covering these aspects is described in two parts. First bayes updating is used to estimate the parameters of the corrosion distribution for each unique environment. The second part uses this resulting distribution and describes how this distribution develops with time. The model is demonstrated with an example and compared to similar spatio-temporal models. The model is promising for improvement from simplistic uniform description of surface and linear progression used in current industry practice.
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