首页|Prediction of long-term localized corrosion rates in a carbon steel cooling water system is enhanced by metagenome analysis

Prediction of long-term localized corrosion rates in a carbon steel cooling water system is enhanced by metagenome analysis

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  • NSTL
  • Elsevier
To predict variation of maximum localized penetration with exposure time, long-term localized corrosion was assessed in an emergency cooling water system composed of two carbon steel pipelines of 700 mm diameter transporting raw river water at flow velocities of 1 m/s and 0.1 m/ s.Field tests, visual inspection, ultrasonic testing, BART testing, SEM-EDS and metagenomic analyses were performed to assess the progress of long-term corrosion and determine the influ-ence of microbes in the corrosion process.High corrosion was linked to sulphate reducing bacteria and potentially to methanogenic archaea in the low-velocity pipeline, while moderate corrosion was linked to non-sulphate reducing bacteria in the higher velocity pipeline. Using historical and literature data available as well as our own test results, an empirical model was developed to predict Maximum Localized Penetration change over time to be applied in the ageing management of cooling water systems.Molecular Microbiological Methods in combination with traditional techniques are useful tools in the ageing management of pipelines. By applying the empirical model developed and the approach presented, unexpected through-wall leaking can be avoided, thus, saving costs and assets.

Mechanical engineeringEmergency cooling water pipelineCarbon steelMolecular microbiological methodsMicrobiologically influenced corrosionSulphate reducing bacteriamethanogensageing managementMICROBIOLOGICALLY INFLUENCED CORROSIONSULFATE-REDUCING BACTERIAIRON-CORROSIONGAS-INDUSTRYTUBERCLESOILEXTRACTIONPIPELINESPROGRESSARCHAEA

Gosi, Peter、Ratkai, Sandor、Shetty, Prateek、Wirth, Roland、Maroti, Gergely、Oszvald, Ferenc、Knisz, Judit

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Univ Publ Serv

MVM Paks Nucl Power Plant

Biol Res Ctr

2022

10.1016/j.engfailanal.2022.106733

Engineering failure analysis

Engineering failure analysis

EISCI
ISSN：1350-6307
年,卷(期)：2022.141
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