Investigation of the Actual Inspection Data for Corrosion Under Insulation (CUI) in Chemical Plant and Examination about Estimation Method for Likelihood of CUI

Kurihara, Tomoyuki; Miyake, Ryusuke; Oshima, Norio; Nakahara, Masao

doi:10.3323/jcorr.59.291

Cited by 10 publications

(4 citation statements)

References 3 publications

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“…These a little bit higher CUI corrosion rates are warmly admissible due to two main reasons; (i) API 581 data is experimental data which has been obtained under controlled situations [11]. Kurihara et al [12] in his research has proved that field data subject to CUI corrosion rates is always higher than the API 581 published corrosion rates. When the facts and figures of his research work was deeply evaluated by the authors, its came to know that on an average, field data corrosion rates were 7% more than API 581 published corrosion rates.…”

Section: Cui Corrosion Rates Obtained From Developed Fuzzy Logic Modelmentioning

confidence: 99%

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

et al. 2018

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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.

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Section: Cui Corrosion Rates Obtained From Developed Fuzzy Logic Modelmentioning

confidence: 99%

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

et al. 2018

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“…The horizontal axis k mean and the vertical axis R mean t are calculated in reference to Eqs. (18) and (19) using the mean value of each parameter.…”

Section: Definition Of Limit State and Summary Of The Variables For Tmentioning

confidence: 99%

Sensitivity Analysis of Fitness-For-Service Assessment Based on Reliability for Cylindrical Pressure Vessels With Local Metal Loss

Kaida

Izumi

Sakai

2012

Volume 7: Operations, Applications and Components

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The concern with Fitness-For-Service (FFS) assessment using stochastic analysis for aged pressure equipments with local metal loss has been growing for the last several years. The structural integrity assessment based on reliability helps to make a decision as to whether to run or repair the equipments with local metal loss. As for analysis of failure probability, it is important to clear which variables affect highly the structural integrity. The stochastic property of the influential parameter needs to be clarified. There has, however, been little study to analyze quantitatively the sensitivity of the parameters for the FFS assessment of the components with local metal loss. In this study, the effects of parameters on plastic collapse of the damaged component were evaluated utilizing parameter sensitivity study. Additionally, sensitivity indices for the component with several shapes of local metal loss were analyzed. It was found from the results that the corrosion rate has much influence on probability of failure. Finally, practical stochastic analysis procedure for the component with local metal loss was proposed. In the proposed procedure, the parameter which has consistently low sensitivity to limit state was used as constant value.

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“…Regarding the corrosion rate C v , Kurihara et al investigated the corrosion rate of CUI using actual inspection data [19]. They found that the distribution of corrosion rate for CUI fitted the Type I extreme value distribution of the largest value.…”

Section: Definition Of Limitmentioning

confidence: 99%

Sensitivity Analysis of Fitness-for-Service Assessment Based on Reliability for Cylindrical Pressure Vessels With Local Metal Loss

Kaida

Izumi²,

Sakai

2013

Journal of Pressure Vessel Technology

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Concern about fitness-for-service (FFS) assessments using stochastic analyses for aged pressure equipment with local metal loss has been growing. When a decision must be made regarding whether to run or repair equipment with local metal loss, a structural integrity assessment based on reliability helps. In analyses of failure probability, it is important to identify which variables strongly affect the structural integrity. The stochastic properties of influential parameters must be clarified, but few data have been published regarding the quantitative analysis of the sensitivity of the parameters in FFS assessments of components with local metal loss. Here, we investigated the effects of parameters on the plastic collapse of a damaged cylindrical pressure vessel with local metal loss, in an evaluation of parameter sensitivity. We also analyzed sensitivity indices for the component with several shapes of local metal loss. We found that the corrosion rate has a major influence on the probability of failure. We propose a practical stochastic analysis procedure for components with local metal loss. In this procedure, the parameter that has consistently low sensitivity to the limit state is used as a constant value.

show abstract

Investigation of the Actual Inspection Data for Corrosion Under Insulation (CUI) in Chemical Plant and Examination about Estimation Method for Likelihood of CUI

Cited by 10 publications

References 3 publications

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

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

Sensitivity Analysis of Fitness-For-Service Assessment Based on Reliability for Cylindrical Pressure Vessels With Local Metal Loss

Sensitivity Analysis of Fitness-for-Service Assessment Based on Reliability for Cylindrical Pressure Vessels With Local Metal Loss

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