A predictive approach to fitness-for-service assessment of pitting corrosion

Shekari, Elahe; Khan, Faisal; Ahmed, Salim

doi:10.1016/j.ijpvp.2015.04.014

Cited by 23 publications

(11 citation statements)

References 15 publications

(30 reference statements)

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“…The values used in the relations above are Table 4). To calculate the probability of failure FP i of the defect i, the Monte Carlo method [5,18] was used.…”

Section: Fault Diagnosis and Detectionmentioning

confidence: 99%

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Detection and Analysis of Petroleum Equipment Faults

Minescu¹,

Pana²

2017

Fault Diagnosis and Detection

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The method fitness-for-service (FFS) provides the means by which the operator of a technical system can decide: It can continue to work safely, reducing of working parameters or stopping the equipment and reparation it. A case study concerning a natural gas pipeline is introduced. It brings some applicative aspects: the introduction of the failure probability as an indicator; the reduction of the degree of conservatism; a maintenance program based on pipeline intelligent gauge.

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“…The values used in the relations above are Table 4). To calculate the probability of failure FP i of the defect i, the Monte Carlo method [5,18] was used.…”

Section: Fault Diagnosis and Detectionmentioning

confidence: 99%

“…Many papers are devoted to this topic. Shekari et al [5] have used FFS assessment methodology for process equipment to track and predict pitting corrosion. Pit density was modeled using a non-homogenous Poisson process and induction time for pit initiation is simulated as the realization of a Weibull process.…”

Section: Introductionmentioning

confidence: 99%

Detection and Analysis of Petroleum Equipment Faults

Minescu¹,

Pana²

2017

Fault Diagnosis and Detection

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“…In another study, this time aimed at establishing a predictive fitness-for-service (FFS) assessment of pitting corrosion, authors Shekari, Khan, and Ahmed [119] developed a new model also relying on a non-homogeneous Markov system. This process is commonly utilized in pitting corrosion modeling due to the random nature of its initiation.…”

Section: Predictive Modeling Of Pitting Corrosionmentioning

confidence: 99%

Framework for Structural Online Health Monitoring of Aging and Degradation of Secondary Systems due to some Aspects of Erosion

Gribok¹,

Patnaik²,

Williams³

et al. 2016

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This report describes the current state of research related to critical aspects of erosion and selected aspects of degradation of secondary components in nuclear power plants (NPPs). The report also proposes a framework for online health monitoring of aging and degradation of secondary components. The framework consists of an integrated multi-sensor modality system, which can be used to monitor different piping configurations under different degradation conditions. The report analyses the currently known degradation mechanisms and available predictive models. Based on this analysis, the structural health monitoring framework is proposed. The Light Water Reactor Sustainability Program began to evaluate technologies that could be used to perform online monitoring of piping and other secondary system structural components in commercial NPPs. These online monitoring systems have the potential to identify when a more-detailed inspection is needed using real-time measurements, rather than at a predetermined inspection interval. This transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. There is unanimous agreement between industry experts and academic researchers that identifying and prioritizing inspection locations in secondary piping systems (for example, in raw water piping or diesel piping) would eliminate many excessive in-service inspections. The proposed structural health monitoring framework takes aim at answering this challenge by combining long-range guided wave technologies with other monitoring techniques, which can significantly increase the inspection length and pinpoint the locations that degraded the most. More widely, the report suggests research efforts aimed at developing, validating, and deploying online corrosion monitoring techniques for complex geometries, which are pervasive in NPPs.

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“…Statistical approaches are used by many academics to forecast the evolution of corrosion pits. Corrosion pit depth can be described by Gauss distribution, [ 18 ] Poisson distribution, [ 19 ] Gamma distribution, [ 20 ] and extreme value distribution. [ 21 ] Liu et al [ 22 ] used Weibull and Gumbel distribution functions to investigate corrosion pit initiation and growth, and discovered that decreasing the Mo element boosted the passivation rate of stainless steel.…”

Section: Introductionmentioning

confidence: 99%

Experimental study of corrosion behavior on 7005 aluminum alloy under acidic 3.5 wt% NaCl environment

Wang

Kou

et al. 2023

Materials & Corrosion

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The corrosion failure behavior of 7005 aluminum alloy is a critical issue in the durability studies of vessels operating. In this study, the corrosion behavior of aluminum alloy 7005‐T4 in 3.5 wt% NaCl solution with pH 2, pH 4, and pH 6 was investigated by surface observation, electrochemical, and mechanical testing. The experiment results that the corrosion susceptibility is more at a solution of pH 2 compared with that at pH 4 and pH 6. The maximum depth and width of corrosion pits increase linearly with aggravation of corrosion. In addition, the probability distribution of the corrosion pit depth in each corrosion environment, which generally follows a Lognormal distribution, is statistically analyzed. The tendency of stress−strain curves at the elastic−plastic transition stage indicated that corrosion has an effect on mechanical performance, and revealed that corrosion promotes the advance of the plastic deformation stage. Fractography indicated the presence of a quasi‐cleavage zone beneath the corrosion layer. The results provide theoretical guidance for safe service and design guidelines for 7005 aluminum alloy.

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A predictive approach to fitness-for-service assessment of pitting corrosion

Cited by 23 publications

References 15 publications

Detection and Analysis of Petroleum Equipment Faults

Detection and Analysis of Petroleum Equipment Faults

Framework for Structural Online Health Monitoring of Aging and Degradation of Secondary Systems due to some Aspects of Erosion

Experimental study of corrosion behavior on 7005 aluminum alloy under acidic 3.5 wt% NaCl environment

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