Influence of Organic Matter/Bacteria on the Formation and Transformation of Sulfate Green Rust

Duboscq, Julien; Vincent, Julia; Jeannin, Marc; Sabot, R.; Lanneluc, Isabelle; Sablé, Sophie; Refait, Philippe

doi:10.3390/cmd3010001

Cited by 3 publications

(1 citation statement)

References 45 publications

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“…In general, coating failure occurs due to an electrochemical reaction beneath the coating. In aggressive coastal marine environments, the causes of coating failures of offshore pipelines can be divided into the following two categories: corrosion due to microorganism activity [ 1 , 2 , 3 ] and maritime activities, including wet–dry cyclic conditions such as those at splash zone areas [ 4 ], and other/unknown causes [ 5 ]. In the aerospace industry, exterior coating failure occurs due to the high temperatures of engine exhausts and the drag effect of atmospheric friction [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Failure Severity Prediction for Protective-Coating Disbondment via the Classification of Acoustic Emission Signals

Rahman

May

Jaffari

et al. 2023

Sensors

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Structural health monitoring is a popular inspection method that utilizes acoustic emission (AE) signals for fault detection in engineering infrastructures. Diagnosis based on the propagation of AE signals along any surface material offers an attractive solution for fault identification. However, the classification of AE signals originating from failure events, especially coating failure (coating disbondment), is a challenging task given the AE signature of each material. Thus, different experimental settings and analyses of AE signals are required to classify the various types of coating failures, and they are time-consuming and expensive. Hence, to address these issues, we utilized machine learning (ML) classification models in this work to evaluate epoxy-based-protective-coating disbondment based on the AE principle. A coating disbondment experiment consisting of coated carbon steel test panels for the collection of AE signals was implemented. The obtained AE signals were then processed to construct the final dataset to train various state-of-the-art ML classification models to divide the failure severity of coating disbondment into three classes. Consequently, methods for the extraction of useful features, the handling of data imbalance, and a reduction in the bias of ML models were also effectively utilized in this study. Evaluations of state-of-the-art ML classification models on the AE signal dataset in terms of standard metrics revealed that the decision forest classification model outperformed the other state-of-the-art models, with accuracy, precision, recall, and F1 score values of 99.48%, 98.76%, 97.58%, and 98.17%, respectively. These results demonstrate the effectiveness of utilizing ML classification models for the failure severity prediction of protective-coating defects via AE signals.

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Section: Introductionmentioning

confidence: 99%

Failure Severity Prediction for Protective-Coating Disbondment via the Classification of Acoustic Emission Signals

Rahman

May

Jaffari

et al. 2023

Sensors

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Iron precipitation under controlled oxygen flow: Mineralogical implications for BIF precursors in the Archean ocean

Chorney

Chemtob

2023

Chemical Geology

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Cathodic protection of carbon steel in thin layers of seawater

Génin

Jeannin

Grolleau

et al. 2023

ACMM

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Purpose The purpose of this study is to investigate cathodic protection (CP) efficiency in the tidal zone and its associated processes. Design/methodology/approach Specific features of CP in the tidal zone, that is, persistence of a thin seawater film and insufficient cathodic potential due to ohmic drop, were addressed. In this preliminary study, carbon steel electrodes were polarized at two cathodic potentials (correct or insufficient protection) while immersed in 1 mm or 5 mm thick natural seawater layers. After CP interruption, the protective ability of the layers covering the steel electrodes was studied using various electrochemical methods, including electrochemical impedance spectroscopy. The layers were characterized by XRD. Findings The protective ability of calcareous deposits was increased in thin seawater films. Insufficient CP could promote protective aragonite/corrosion products layer. Originality/value The combined effects of thin seawater film and applied potential were never addressed, and the conclusions drawn from this preliminary study give new insight on the efficiency of CP in the tidal zone.

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Influence of Organic Matter/Bacteria on the Formation and Transformation of Sulfate Green Rust

Cited by 3 publications

References 45 publications

Failure Severity Prediction for Protective-Coating Disbondment via the Classification of Acoustic Emission Signals

Failure Severity Prediction for Protective-Coating Disbondment via the Classification of Acoustic Emission Signals

Iron precipitation under controlled oxygen flow: Mineralogical implications for BIF precursors in the Archean ocean

Cathodic protection of carbon steel in thin layers of seawater

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