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Statistical Approach for Corrosion Prediction Under Fuzzy Soil Environment
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  • Journal title : Environmental Engineering Research
  • Volume 18, Issue 1,  2013, pp.37-43
  • Publisher : Korean Society of Environmental Engineering
  • DOI : 10.4491/eer.2013.18.1.037
 Title & Authors
Statistical Approach for Corrosion Prediction Under Fuzzy Soil Environment
Kim, Mincheol; Inakazu, Toyono; Koizumi, Akira; Koo, Jayong;
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Water distribution pipes installed underground have potential risks of pipe failure and burst. After years of use, pipe walls tend to be corroded due to aggressive soil environments where they are located. The present study aims to assess the degree of external corrosion of a distribution pipe network. In situ data obtained through test pit excavation and direct sampling are carefully collated and assessed. A statistical approach is useful to predict severity of pipe corrosion at present and in future. First, criteria functions defined by discriminant function analysis are formulated to judge whether the pipes are seriously corroded. Data utilized in the analyses are those related to soil property, i.e., soil resistivity, pH, water content, and chloride ion. Secondly, corrosion factors that significantly affect pipe wall pitting (vertical) and spread (horizontal) on the pipe surface are identified with a view to quantifying a degree of the pipe corrosion. Finally, a most reliable model represented in the form of a multiple regression equation is developed for this purpose. From these analyses, it can be concluded that our proposed model is effective to predict the severity and rate of pipe corrosion utilizing selected factors that reflect the fuzzy soil environment.
Discriminant function;Distribution pipe;External corrosion;Regression analysis;Replacement plan;Soil properties;
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Continuous electrochemical removal of salts from Korean food wastes, Journal of the Taiwan Institute of Chemical Engineers, 2016, 64, 142  crossref(new windwow)
Decker JB, Rollins KM, Ellsworth JC. Corrosion rate evaluation and prediction for piles based on long-term field performance. J. Geotech. Geoenviron. Eng. 2008;134:341-351. crossref(new window)

Japan Ductile Iron Pipe Association (JDPA). Technical report about the factors of corrosion and anticorrosion measures for buried pipes. Tokyo: JDPA; 2001. p. 2-7.

Romer AE, Bell GE. Causes of external corrosion on buried water mains. In: Castronovo JP, ed. Pipelines 2001: advances in pipelines engineering and construction. Reston: American Society of Civil Engineers; 2001. p. 1-9.

Sarin P, Snoeyink VL, Lytle DA, Kriven WM. Iron corrosion scales: model for scales growth, iron release, and colored water formation. J. Environ. Eng. 2004;130:364-373. crossref(new window)

Katano Y, Miyata K, Shimizu H, Isogai T. Predictive model for pit growth on underground pipes. Corrosion 2003;59:155-161. crossref(new window)

Kolovich K, Kiefner JF. Calculation of a corrosion rate using Monte Carlo simulation. In: Proceedings of NACE International Corrosion 2007 Conference and Expo; 2007 Mar 11-15; Nashville, TN. p. 176-182.

Restrepo A, Delgado J, Echeverria F. Evaluation of current condition and lifespan of drinking water pipelines. J. Fail. Anal. Prev. 2009;9:541-548. crossref(new window)

Suwon Metropolitan Waterworks. The technical analysis of water supply system in Suwon. Suwon: Suwon Metropolitan Waterworks; 2010. p. 247-286.

Choi TH, Lee SW, Koizumi A, Koo JY. Reliability assessment of water distribution systems using management reliability index. In: Proceedings of of the 4th IWA Leading-Edge Strategic Asset Management (LESAM 2011); 2011 Sep 27-30; Mulheim, Germany. London: IWA; 2011. p. 1-9.

Arai Y, Koizumi A, Umano H, Ashida H, Ozaki M, Yoshida E. Statistical analysis of the corrosion of water distribution pipes under their environmental factors. J. Jpn. Soc. Civ. Eng. Environ. Syst. Res. 2009;37:9-17.

Cleyo F, Velazquez JC, Valor A, Hallen JM. Probability distribution of pitting corrosion depth and rate in underground pipelines: a Monte Carlo study. Corros. Sci. 2009;51:1925- 1934. crossref(new window)