The Effect of Chlorine Ion on Metal Corrosion Behavior under the Scratch Defect of Coating

Cui, Yanyu; Qin, Yongxiang; Dilimulati, Dilinuer; Wang, Yujun

doi:10.1155/2019/7982893

Cited by 11 publications

(5 citation statements)

References 6 publications

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“…It was found that the corrosion rate was increased with the increment of Cl − . It can be attributed to the reason that the passivation film of steel can be damaged by chloride ions in the process of competing with hydrogen and oxygen ions in the absorption process, thus causing the occurrence of pitting corrosion [58].…”

Section: Effect Of the Average Chloridementioning

confidence: 99%

A Machine Learning‐Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel

Tran

Nguyen

Phan

et al. 2021

Advances in Materials Science and Engineering

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The purpose of this study is to develop a practical artificial neural network (ANN) model for predicting the atmospheric corrosion rate of carbon steel. A set of 240 data samples, which are collected from the experimental results of atmospheric corrosion in tropical climate conditions, are utilized to develop the ANN model. Accordingly, seven meteorological and chemical factors of corrosion, namely, the average temperature, the average relative humidity, the total rainfall, the time of wetness, the hours of sunshine, the average chloride ion concentration, and the average sulfur dioxide deposition rate, are used as input variables for the ANN model. Meanwhile, the atmospheric corrosion rate of carbon steel is considered as the output variable. An optimal ANN model with a high coefficient of determination of 0.999 and a small root mean square error of 0.281 mg/m2.month is retained to predict the corrosion rate. Moreover, the sensitivity analysis shows that the rainfall and hours of sunshine are the most influential parameters on predicting the atmospheric corrosion rate, whereas the average chloride ion concentration, the average temperature, and the time of wetness are less sensitive to the atmospheric corrosion rate. An ANN-based formula, which accommodates all input parameters, is thereafter proposed to estimate the atmospheric corrosion rate of carbon steel. Finally, a graphical user interface is developed for calculating the atmospheric corrosion rate of carbon steel in tropical climate conditions.

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Section: Effect Of the Average Chloridementioning

confidence: 99%

A Machine Learning‐Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel

Tran

Nguyen

Phan

et al. 2021

Advances in Materials Science and Engineering

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“…Tindak balas keluli seperti 316L dalam larutan yang mengandungi H2S dipengaruhi oleh faktor interaksi bahan (Zhang et al 2017), struktur mikro (Hashim et al 2019), saiz bahan (Aghuy et al 2015) dan juga faktor persekitaran yang merujuk kepada tekanan separa H2S ). Selain itu, kepekatan ion klorida (Cui et al 2019), pH , suhu (Handoko et al 2019), masa pendedahan (Melchers et al 2019) dan tekanan persekitaran (Nazarov et al 2019) turut mempengaruhi kelakuan kakisan keluli berkarbon rendah ini. Namun begitu, kajian kakisan yang melibatkan kesan gas H2S didapati masih di peringkat permulaan berbanding kajian kakisan yang berpunca daripada gas karbon dioksida (CO2) kerana kesukaran untuk bekerja di persekitaran yang mengandungi gas H2S ).…”

Section: Pendahuluanunclassified

Effect of Ph2s Influence on Austenitic Stainless Steel 316l Corrosion Behaviours in Chloride Environment / Kesan Pengaruh Tekanan Separa Gas H2s Terhadap Tingkah Laku Kakisan Keluli Tahan Karat 316l Di Persekitaran Klorida

Shah

Manap

Ayob

et al. 2021

MJCE

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H2S corrosion of equipment and pipeline system failures in oil and gas industry is a major concern of researchers as it involves high maintenance costs. Therefore, this study discusses the effect of H2S partial pressure at 0, 3 and 15 bar towards the corrosion behaviour of 316L austenitic stainless steel in chloride environments. The 316L steel exposed to 0 bar pH2S was slightly corroded due to the presence of Cr element which has increased the corrosion resistance of the 316L steel. However, pit penetration rate of 316L steel was increased by 90.1% from 0.07 mm/year at 0 bar pH2S to 0.74 mm/year at 3 bar pH2S and decreased by 83.2% at 15 bar pH2S due to the saturated sulfide content in the test solution. Therefore, 316L steel at 3 bar shows highest corrosion effect due to the dissolution of Cr element at 316L steels surface, thus enhanced passive film breakdown.

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“…This measure slowed the corrosion rate to a certain extent, but the corrosion problem still exists. In addition, if the anticorrosion layer has defects such as shedding, the corrosion rate of the buried pipeline will be further accelerated [3,[13][14][15]. According to investigations, sulfate reducing bacteria, iron bacteria, iron oxidizing bacteria, and sulfur oxidizing bacteria have a great influence on metal corrosion, and SRB is considered to be one of the most influential microorganisms [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Study on corrosion behavior of X80 steel under stripping coating by sulfate reducing bacteria

2021

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Background At present, microorganism has been considered as important factors that threaten to buried pipelines with disbonded coatings. Aiming at the problem of unknown corrosion mechanism of sulfate-reducing bacteria (SRB), a series of studies have been carried out in this paper. Spectrophotometer and fluorescent labeling technology are used to study the growth and attachment of SRB in the simulated soil solution. The corrosion behavior of X80 pipeline steel with or without SRB was researched by electrochemical methods such as open circuit potential, dynamic potential polarization curve, and electrochemical impedance spectroscopy. The microscopic morphology of the corrosion products on the surface was observed with a scanning electron microscope (SEM), and the element content of the corrosion products on the surface of the sample after corrosion was observed using X-ray energy spectrum (EDS) analysis. Results The results showed that the growth and reproduction of SRB caused the pH of the soil simulated solution to increase, which may promote the corrosion of X80 steel. In addition, the cathode reaction of X80 steel in a sterile environment is the reduction of H+, and the main corrosion product is iron oxide. When the soil simulation solution contains SRB, the cathodic reaction is controlled by both H+ reduction and sulfide depolarization reactions, and FeS appears in the corrosion products. Conclusion Although the life cycle of SRB is only about 14 days, the corrosion of X80 steel is greatly promoted by SRB, and even causes corrosion perforation, which will bring huge economic losses and serious safety hazards.

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The Effect of Chlorine Ion on Metal Corrosion Behavior under the Scratch Defect of Coating

Cited by 11 publications

References 6 publications

A Machine Learning‐Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel

A Machine Learning‐Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel

Effect of Ph2s Influence on Austenitic Stainless Steel 316l Corrosion Behaviours in Chloride Environment / Kesan Pengaruh Tekanan Separa Gas H2s Terhadap Tingkah Laku Kakisan Keluli Tahan Karat 316l Di Persekitaran Klorida

Study on corrosion behavior of X80 steel under stripping coating by sulfate reducing bacteria

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