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Modeling microbiologically influenced corrosion of N-80 carbon steel by fuzzy calculus

Abstract

To investigate microbiologically influenced corrosion (MIC) risk using fuzzy Iogics, weight loss study of N-80 steel was carried out under three circumstances: (1) abiotic, (2) completely biotic (no biocide), and (3) biotic with almost enough biocide (underlined are fuzzy expressions). The microorganism employed was sulphate-reducing bacteria (SRB). Also, effective concentration of a biocide to kill the bacteria was investigated and recorded. Using fuzzy logics and calculus, it was shown that (fuzzy) probability of risk of MIC in the biotic system without biocide was 60 pct, whereas with almost enough biocide, the risk was 50 pct. Different from being absolute risk values, these risk values showed that fuzzy logics methods had the capability of showing how vulnerable a system could be to MIC.

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Abbreviations

⊕:

Operator minimum, implying that the method uses minimum membership functions from the given fuzz sets.

◯:

Operator maximum-minimum, showing that from minimum values of membership functions, maximum values will be selected.

U 1, V 1, and U 2 :

The universal sets that contain variables such as biocide concentration, β, risk of MIC, r, and corrosion rate, C, respectively.

A 1, A 2, B 1, A*1, and A*2 :

Fuzzy sets containing fuzzy values or membership functions for each element of the universal sets.

P :

The fuzzy rule that explains relationships between certain values in a fuzzy manner.

P 1 and P 2 :

Fuzzy rules defined for certain memberships such as biocide concentration or corrosion rate to relate them to risk of MIC.

P* 1 and P* 2 :

Fuzzy observations addressing the member-ships in a fuzzy manner.

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Javaherdashti, R. Modeling microbiologically influenced corrosion of N-80 carbon steel by fuzzy calculus. Metall Mater Trans A 35, 2051–2056 (2004). https://doi.org/10.1007/s11661-004-0153-1

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Keywords

  • Material Transaction
  • Corrosion Rate
  • Fuzzy Logic
  • Carbon Steel
  • Fuzzy Rule