Prediction for CUI in Piping Systems using Fuzzy Logic with Sensitivity Analysis of Corrosion Producing Factors

Corrosion under insulation (CUI) is a progressive problem for piping systems in oil and gas industries especially in petrochemical and chemical plants due to its catastrophic disasters and consequently its automatic impact on the environment. To ensure CUI problem should not spark sudden surprise in...

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Main Authors: Khan Muhammad Mohsin, Mokhtar Ainul Akmar, Hussin Hilmi, Muhammad Masdi
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201822506002
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spelling doaj-40a914f4ad6d42a4babe5bb3afaadb3d2021-03-02T09:47:38ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-012250600210.1051/matecconf/201822506002matecconf_ses2018_06002Prediction for CUI in Piping Systems using Fuzzy Logic with Sensitivity Analysis of Corrosion Producing FactorsKhan Muhammad MohsinMokhtar Ainul AkmarHussin HilmiMuhammad MasdiCorrosion under insulation (CUI) is a progressive problem for piping systems in oil and gas industries especially in petrochemical and chemical plants due to its catastrophic disasters and consequently its automatic impact on the environment. To ensure CUI problem should not spark sudden surprise in plants, indeterminate factors that contribute to the deterioration of pipes subject to CUI should be recognized and taken care seriously. Operating temperature, type of environment, insulation type, pipe complexity and insulation condition of the pipes are the key factors that cause significant deterioration of pipes due to CUI. As per its varying nature, CUI is difficult to predict as it remains hidden beneath the insulation and gets growth in an ambiguous and abrupt manner. For such an uncertain and critical situation, fuzzy logic is a good choice to be deal with. Thus, in this study, CUI corrosion rate for insulated carbon steel piping systems has been predicted by fuzzy logic using API 581 data. Predicted CUI corrosion rates obtained by the developed fuzzy logic model are committing quite satisfactory results when comparing with API 581 published CUI corrosion rates. At the end of study, sensitivity analysis (SA) of CUI producing factors has also been performed. SA is showing the role of each CUI producing factor in terms of percentage, having participation for the cause of 1 mm/year CUI in pipes. The predicted CUI corrosion rates and SA will help inspection engineers for setting and delivering the risk-based inspection priority for insulated piping systems at their concerned plants.https://doi.org/10.1051/matecconf/201822506002
collection DOAJ
language English
format Article
sources DOAJ
author Khan Muhammad Mohsin
Mokhtar Ainul Akmar
Hussin Hilmi
Muhammad Masdi
spellingShingle Khan Muhammad Mohsin
Mokhtar Ainul Akmar
Hussin Hilmi
Muhammad Masdi
Prediction for CUI in Piping Systems using Fuzzy Logic with Sensitivity Analysis of Corrosion Producing Factors
MATEC Web of Conferences
author_facet Khan Muhammad Mohsin
Mokhtar Ainul Akmar
Hussin Hilmi
Muhammad Masdi
author_sort Khan Muhammad Mohsin
title Prediction for CUI in Piping Systems using Fuzzy Logic with Sensitivity Analysis of Corrosion Producing Factors
title_short Prediction for CUI in Piping Systems using Fuzzy Logic with Sensitivity Analysis of Corrosion Producing Factors
title_full Prediction for CUI in Piping Systems using Fuzzy Logic with Sensitivity Analysis of Corrosion Producing Factors
title_fullStr Prediction for CUI in Piping Systems using Fuzzy Logic with Sensitivity Analysis of Corrosion Producing Factors
title_full_unstemmed Prediction for CUI in Piping Systems using Fuzzy Logic with Sensitivity Analysis of Corrosion Producing Factors
title_sort prediction for cui in piping systems using fuzzy logic with sensitivity analysis of corrosion producing factors
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2018-01-01
description Corrosion under insulation (CUI) is a progressive problem for piping systems in oil and gas industries especially in petrochemical and chemical plants due to its catastrophic disasters and consequently its automatic impact on the environment. To ensure CUI problem should not spark sudden surprise in plants, indeterminate factors that contribute to the deterioration of pipes subject to CUI should be recognized and taken care seriously. Operating temperature, type of environment, insulation type, pipe complexity and insulation condition of the pipes are the key factors that cause significant deterioration of pipes due to CUI. As per its varying nature, CUI is difficult to predict as it remains hidden beneath the insulation and gets growth in an ambiguous and abrupt manner. For such an uncertain and critical situation, fuzzy logic is a good choice to be deal with. Thus, in this study, CUI corrosion rate for insulated carbon steel piping systems has been predicted by fuzzy logic using API 581 data. Predicted CUI corrosion rates obtained by the developed fuzzy logic model are committing quite satisfactory results when comparing with API 581 published CUI corrosion rates. At the end of study, sensitivity analysis (SA) of CUI producing factors has also been performed. SA is showing the role of each CUI producing factor in terms of percentage, having participation for the cause of 1 mm/year CUI in pipes. The predicted CUI corrosion rates and SA will help inspection engineers for setting and delivering the risk-based inspection priority for insulated piping systems at their concerned plants.
url https://doi.org/10.1051/matecconf/201822506002
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