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Research Papers

Probabilistic Modeling of Pitting Corrosion in Insulated Components Operating in Offshore Facilities

[+] Author and Article Information
Elahe Shekari

Centre for Risk, Integrity and Safety Engineering (C-RISE),
Department of Process Engineering,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John’s, NL A1B 3X5, Canada
e-mail: e.shekari@mun.ca

Faisal Khan

Centre for Risk, Integrity and Safety Engineering (C-RISE),
Department of Process Engineering,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John’s, NL A1B 3X5, Canada
e-mail: fikhan@mun.ca

Salim Ahmed

Centre for Risk, Integrity and Safety Engineering (C-RISE),
Department of Process Engineering,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John’s, NL A1B 3X5, Canada
e-mail: sahmed@mun.ca

1Corresponding author.

Manuscript received February 14, 2016; final manuscript received August 28, 2016; published online November 21, 2016. Assoc. Editor: Mohammad Pourgol-Mohammad.

ASME J. Risk Uncertainty Part B 3(1), 011003 (Nov 21, 2016) (11 pages) Paper No: RISK-16-1054; doi: 10.1115/1.4034603 History: Received February 14, 2016; Accepted August 28, 2016

Pitting corrosion under insulation is one of the challenging issues for safe operation of offshore facilities. Degradation usually remains hidden causing the inspection of insulated assets to be equally challenging. The modeling of the pitting corrosion under insulation (CUI) helps us to better understand the current state of the asset and predict failure. This paper investigates the factors affecting the pit initiation and pit growth on equipment under insulation operating in offshore environments. A methodology is proposed for studying the pitting CUI characteristics, including pit initiation time, pit density, and maximum pit depth over time. The proposed methodology provides a practical and more effective asset life management approach when supported by inspection data. The practical application of the proposed methodology is demonstrated in this paper using a pressure vessel case study in an offshore platform.

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References

Figures

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Fig. 1

The methodology for evaluation of pitting CUI modeling

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Fig. 2

Schematic representation of maximum pit growth in an insulated component using Markov process, adopted from [11]

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Fig. 3

The estimated average maximum pit depth and observed values of maximum pit depth reported by Aziz’s pitting corrosion test [32]

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Fig. 4

Average pit density for 15 years

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Fig. 5

(a) The PDF of maximum pit depth in different years and (b) the CDF of maximum pit depth in different years

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Fig. 6

Maximum pit depth for 15 years

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Fig. 7

Average pit density models

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Fig. 8

Average maximum pit depth for different APD models

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Fig. 9

Mean maximum pit depth in different values of ω

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Fig. 10

Mean maximum pit depth in different values of χ

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Fig. 11

Schematic representation of the expected pitting damage after 5 and 15 years

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