On the Use of the Generalized Lambda Distribution and Parametric Bootstrap Method in the Prediction of Maximum Pit Depths: Comparison With Experimental Pipeline Data

2010 ◽  
Author(s):  
L. Alfonso ◽  
F. Caleyo ◽  
J. M. Hallen ◽  
J. Araujo
Keyword(s):  
Pitting Corrosion ◽  
Extreme Values ◽  
Pipeline Steel ◽  
Bootstrap Method ◽  
Real Life ◽  
Bootstrap Sample ◽  
Generalized Lambda Distribution ◽  
Bootstrap Estimate ◽  
Pit Depth ◽  
Corrosion Data

The approach proposed by Najjar and coworkers for the prediction of maximum pit depth is applied and validated through direct comparison with real pipeline steel pitting corrosion data. This methodology combines the Generalized Lambda Distribution (GLD) and the Bootstrap Method (BM) in order to estimate both the maximum pit depth and confidence intervals associated with the estimation. Samples are drawn from real-life pitting corrosion data and the GLD is used to obtain modeled pit depth distributions emulating the experimental ones. In order to estimate the maximum pit depth over an N-times larger area, simulated distributions, N-times larger than the experimental ones, are generated 104 times. The deepest pit depth is extracted from each simulated bootstrap sample to obtain a dataset of 104 extreme pit-depth values. An estimate of the maximum pit depth for the N-times larger surface can be obtained from this dataset by calculating the average of the 104 extreme values. The uncertainty in the estimation is derived from the 95% confidence interval of the bootstrap estimate. In this report, the results of the application of the GLD-BM framework are compared with extreme pit depth values observed in real pitting corrosion data. The agreement between the estimated and actual maximum pit depths points to the applicability of the GLD-BM as an alternative in estimating the maximum pit depth when only a small number of samples are available. The main advantage of the combined methodology over the Gumbel method is its great simplicity, since fast and reliable estimations can be made with at least only two experimental samples.

Influence of Remanent Magnetization on Pitting Corrosion in Pipeline Steel

2010 ◽  
Author(s):  
J. H. Espina-Herna´ndez ◽  
F. Caleyo ◽  
J. M. Hallen ◽  
A. Lo´pez-Montenegro ◽  
E. Pe´rez-Baruch
Keyword(s):  
Magnetic Field ◽  
Pitting Corrosion ◽  
Remanent Magnetization ◽  
Pipeline Steel ◽  
Local Magnetic Field ◽  
Extreme Value Analysis ◽  
Pit Depth ◽  
Pipeline Wall ◽  
The Magnetic Field ◽  
Control Samples

These days, in-line inspections based on the magnetic flux leakage (MFL) principle are routinely used to detect and size metal loss and mechanical anomalies in operating oil and gas pipelines. One of the characteristics of the MFL technology is that after the inspection, the pipeline wall shows a remanent magnetization. In this work, the influence of the magnetic field on pitting corrosion in pipeline steel is studied. Pitting corrosion experiments have been carried out on samples of an API 5L grade 52 steel under a magnetization level of the same order of magnitude of the remanent magnetization in the pipeline wall after the MFL inspection. The samples were magnetized using rings of the investigated steel. The closed magnetic circuit configuration used in this study survey guaranteed that the samples kept the same magnetization level during the complete duration of the conducted experiments. This experimental setup was used in order to reproduce the conditions observed in MFL-inspected pipelines in which the magnetic field was confined to the pipe wall thickness. Immediately after magnetization, the investigated samples were subjected to pitting by immersing them in a solution with dissolved Cl− and SO42− ions. The pitting experiments were conducted for exposure times of 7 days. Non-magnetized specimens were used as control samples. The depths of the pits induced in the investigated samples were measured using optical microscopy. The maximum pit depth of each sample was recorded and used to conduct extreme value analysis of the pitting process in the magnetized and non-magnetized specimens. The results of this investigation indicate that the magnetic field confined within the pipeline wall has a significant influence on the pitting corrosion process. The statistical assessment of the pitting corrosion data collected during this study shows that the magnetic field reduces the average depth of the pit population. It also reduces the extreme pit depth values that can be predicted from the maximum values observed in the magnetized samples, with respect to the non-magnetized control samples. Scanning electron microscopy observations show that the magnetic field alters the pit morphology by increasing the pit opening (mouth). It is shown that the observed reduction in the pit depth when a magnetic field is confined to the volume of the corroding material can be explained based on the behavior of the paramagnetic corrosion products under the influence of the local magnetic field gradients produced inside and within the immediate vicinity of stable pits.

Markov Chain Model Helps Predict Pitting Corrosion Depth and Rate in Underground Pipelines

2010 ◽  
Author(s):  
F. Caleyo ◽  
J. C. Vela´zquez ◽  
J. M. Hallen ◽  
A. Valor ◽  
A. Esquivel-Amezcua
Keyword(s):  
Markov Chain ◽  
Pitting Corrosion ◽  
Probability Function ◽  
Markov Chain Model ◽  
Transition Probability ◽  
Real Life ◽  
Chain Model ◽  
Corrosion Depth ◽  
Pit Depth ◽  
Transition Probability Function

A continuous-time, non-homogenous pure birth Markov chain serves to model external pitting corrosion in buried pipelines. The analytical solution of Kolmogorov’s forward equations for this type of Markov process gives the transition probability function in a discrete space of pit depths. The transition probability function can be completely identified by making a correlation between the stochastic pit depth mean and the deterministic mean obtained experimentally. Previously reported Monte Carlo simulations have been used for the prediction of the evolution of the pit depth distribution mean value with time for different soil types. The simulated pit depth distributions are used to develop a stochastic model based on Markov chains to predict the progression of pitting corrosion depth and rate distributions from the observed soil properties and pipeline coating characteristics. The proposed model can also be applied to pitting corrosion data from repeated in-line pipeline inspections. Real-life case studies presented in this work show how pipeline inspection and maintenance planning can be improved through the use of the proposed Markovian model for pitting corrosion.

scholarly journals Pitting Corrosion of Natural Aged Al–Mg–Si Extrusion Profile

Materials ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1081 ◽  
Author(s):  
Quanmei Guan ◽  
Jing Sun ◽  
William Wang ◽  
Junfeng Gao ◽  
Chengxiong Zou ◽  
...  
Keyword(s):  
Pitting Corrosion ◽  
High Speed ◽  
Three Dimensional ◽  
Optical Microscope ◽  
Damage Initiation ◽  
Coarse Grains ◽  
Corrosion Risk ◽  
Heterogeneous Microstructures ◽  
Set Up ◽  
Pit Depth

With the quick development of the high-speed railway and the service of the China Railway High-speed (CRH) series for almost a decade, one of the greatest challenges is the management/maintenance of these trains in environmental conditions. It is critical to estimate pitting damage initiation and accumulation and set up a corresponding database in order to support the foundations for interactive corrosion risk management. In this work, the pitting corrosion of a nature-aged commercial 6005A-T6 aluminum extrusion profile for 200 days was studied comprehensively. The heterogeneous microstructures were conventionally identified by the in situ eddy current, suggesting which investigated regions to fabricate samples for. After constant immersion for 240 h in 3.5 wt % NaCl, the shapes and depths of the pits were captured and measured by optical microscope (OM) and three-dimensional optical profilometry (OP), providing detailed quantification of uniform pitting corrosion. The typical features of the pits dominated by the distribution of precipitates include the peripheral dissolution of the Al matrix, channeling corrosion, intergranular attack, and large pits in the grains. Due to the high density of continuous anodic and cathodic particles constituted by alloying elements in coarse grains, the number of pits in the coarse grains was the highest while the number in the fine grains was the lowest, indicating that fine grains have the best corrosion resistance. The experimental dataset of the pit depth integrated with its corresponding microstructure would set the benchmark for further modeling of the pit depth and the remaining ductility, in order to manage the damage tolerance of the materials.

A Monte Carlo Model for Pitting Corrosion in Phosphor Bronze Tape Used in Underground Power Transmission Cables

CORROSION ◽  
10.5006/3347 ◽  
2020 ◽  
Vol 76 (1) ◽  
pp. 82-92
Author(s):  
Lixin Zhang ◽  
Simon Gill ◽  
Sivashangari Gnanasambandam ◽  
Maurizio Foresta ◽  
Jingzhe Pan ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Pitting Corrosion ◽  
Depth Distribution ◽  
Power Transmission ◽  
Monte Carlo Model ◽  
Probability Of Failure ◽  
Distribution Model ◽  
Pit Depth ◽  
Random Nature

Life of underground oil-filled power transmission cables used with phosphor bronze tapes is greatly reduced by pitting corrosion and hence accurate prediction of the pit growth in these tapes becomes essential. In the present work, the probability distribution of corrosion pit depth on phosphor bronze tapes is calculated using probabilistic Monte Carlo simulations and compared with the measured pit depth distribution on samples of broken tapes which have been in service for about 50 y. This Monte Carlo simulation is performed on every stable pit that nucleates, propagates, and repassivates on the metal surface. Due to the random nature of pitting corrosion, the probability of failure of this class of cables can be simulated based on the Monte Carlo model. This paper shows that the simulated pit depth distribution is very similar to the experimental data. The results demonstrate that the Monte Carlo model by Engelhardt and Macdonald can be effectively applied to long-term field data of phosphor bronze tapes, even over 50 y. In addition, the probability of failure due to pitting corrosion can be evaluated analytically, without need of conducting expensive and time-consuming experimental campaigns. Therefore, this probabilistic pit depth distribution model will be a powerful tool in the decision-making strategy for the replacement of underground power transmission cables near their end of life.

Analysis of the Pitting Corrosion’s Effect on the Residual Strength of Submerged Pressure Shell

2019 ◽  
Author(s):  
Weijun Xu ◽  
Tianyi Chen ◽  
Chenfeng Li ◽  
Xueqian Zhou ◽  
Feng Liu
Keyword(s):  
Finite Element ◽  
Pitting Corrosion ◽  
Residual Strength ◽  
Complex Structure ◽  
Element Model ◽  
Element Analysis ◽  
Influence Coefficients ◽  
The Finite Element Analysis ◽  
Corrosion Pit ◽  
Pit Depth

Abstract Submerged pressure shell’s corrosion situation is more serious due to bad work environment, complex structure and difficulty of maintenance. Based on the analysis of calculation method of submerged pressure shell structures with non-corrosion, the calculation formula of pressure shell with pitting corrosion is given. The Finite Element Model is constructed and its residual strength is investigated. The relationships between shell stress and some parameters, such as radius of corrosion pit, depth of corrosion pit and location of corrosion pit are studied. Based on the finite element analysis results, the effect of radius of corrosion pit on the stress of pressure shell with pitting corrosion is analyzed. Furthermore, the influence coefficients of residual strength of pressure shell due to depth and location of pitting corrosion are determined, which provide a reference for the strength evaluation of submerged pressure shell with pitting corrosion.

Effect of Pitting Corrosion on Strength of AISI 410 Stainless Steel Compressor Blades

2014 ◽  
Vol 606 ◽  
pp. 227-231 ◽  
Author(s):  
Mazmir Mat Noh ◽  
Farzin Mozafari ◽  
Muhammad Adil Khattak ◽  
Mohd Nasir Tamin
Keyword(s):  
Stainless Steel ◽  
Pitting Corrosion ◽  
Tensile Specimen ◽  
Maximum Diameter ◽  
Compressor Blades ◽  
Strength Tests ◽  
Corrosion Pits ◽  
Pit Depth ◽  
Geometry Analysis ◽  
Nucleation Phenomenon

In the present paper, effects of pitting corrosion on the strength of members made of AISI 410 Martensitic stainless steel were investigated. Stainless steel compressor blades in power generation industries commonly suffer from pitting corrosion. Pits geometry analysis and strength tests have been conducted. Pits geometry analysis established the maximum pit depth of 0.26 mm along with the maximum diameter of 1 mm. In addition, strength and elongation of the pitted tensile specimen gradually decrease with the increase of the area lost due to pitting corrosion. A damage nucleation phenomenon at the initial load values is also postulated.

Modeling unpredictable failures of 304 construction material in seawater by pitting corrosion and simulate chloride ion distribution by finite element method

2016 ◽  
Vol 12 (3) ◽  
pp. 543-557 ◽  
Author(s):  
Subir Paul
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Metal Surface ◽  
Pitting Corrosion ◽  
Section Thickness ◽  
Ion Distribution ◽  
Metallic Structures ◽  
Content Type ◽  
Pit Depth ◽  
Over Time

Purpose The purpose of this paper is to predict the life of a corroding metallic structure in seawater so that uncertain and unpredictable failures of a structure, leading to accidents, can be prevented. Design/methodology/approach Pitting has been known to show a large scatter in the measurable parameters such as corrosion rate, maximum pit depth, time to perforation and so on. Scatter results from the influence on pit development on metal surface heterogeneity and from variations in the corrosive environment over time. All these facts suggest that randomness is an inherent and unavoidable characteristic of pitting corrosion over time, so that stochastic models have been developed to formulate pit depth as a function of parameters influencing the process. Since chloride penetrates the passive film of the metal surface, Cl ion distribution into the metal has been mapped by finite element method (FEM). Findings The maximum pit depth which decides the onset of perforation or leakage has been modeled by the following equation: d=36.31(ΔE)0.68×(Δt)0.35. Cl ion distribution within a pit and outside has been modeled for better understanding of pit initiation which till today is not fully understood. Practical implications Perforation and leakage of a tank, container, or pipeline occur when the depth of pitting reaches the section thickness of the material of which the metallic structures are made. The pitting corrosion is localized and occurs at any spot or site where electrochemical conditions (ΔE Equation (9)) are prone to pitting. This leads to unpredictable failures of the structures which may look polished and undamaged under naked eyes. In most metallic structures, pitting may be present at some spots, but failures occur only when the depth predicted by the model Equation (9) reaches the section thickness of the material. Thus, determining pipe to soil potential gives a guide to go for maintenance before pit depth reaches the material thickness, and thereby unpredictable failure can be prevented. Second, the map generated by FEM showing Cl distribution throws much information and light on movement of Cl ions from passive layer into the pit, which leads to its growth. This helps scientists and researchers to understand the mechanism and gives much insights on finding new methods for protection of structures. Social implications The work will guide the engineers and researchers to prevent unpredictable failures of structures leading to accidents and human and property loss and prevent environment pollution from spilling of oil from tank and pipeline. Originality/value This is an original work based on several laboratory-generated simulated experimental data.

Pitting Corrosion of Pipeline Steel in Dilute Bicarbonate Solution with Chloride Ions

CORROSION ◽  
1994 ◽  
Vol 50 (9) ◽  
pp. 651-657 ◽  
Author(s):  
X. Mao ◽  
X. Liu ◽  
R. W. Revie
Keyword(s):  
Pitting Corrosion ◽  
Pipeline Steel ◽  
Chloride Ions
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