Fuzzy-Based Method to Evaluate Soil Corrosivity for Prediction of Water Main Deterioration

Abstract

/npsi/ctrl?lang=en http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?lang=fr Access and use of this website and the material on it are subject to the Terms and Conditions set forth at http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/jsp/nparc_cp.jsp?lang=en NRC Publications Archive Archives des publications du CNRCThis publication could be one of several versions: author's original, accepted manuscript or the publisher's version. / La version de cette publication peut être l'une des suivantes : la version prépublication de l'auteur, la version acceptée du manuscrit ou la version de l'éditeur. For the publisher's version, please access the DOI link below./ Pour consulter la version de l'éditeur, utilisez le lien DOI ci-dessous.http://dx.doi.org/10.1061/(ASCE) 1076-0342(2004)10:4(149) Journal of Infrastructure Systems, 10, 4, pp. 149-156, 2004-12-01 Fuzzy-based method to evaluate soil corrosivity for prediction of water main deterioration Sadiq, R.; Rajani, B. B.; Kleiner, Y. Fuzzy-based method to evaluate soil corrosivity for prediction of water main deterioration A fuzzy-based method is proposed to evaluate soil corrosivity from soil properties such as soil resistivity, pH, redox potential, sulfide content and soil type. The fuzzy-based method considers three levels of soil corrosivity, non-corrosive, moderately corrosive and corrosive. This is in contrast to the commonly used 10-point scoring (10-P) method, which has only two classes, corrosive and non-corrosive. Membership functions for each of the soil properties are used to quantify their affinity to the level of soil corrosivity. These membership values form an evaluation matrix from which a weighted vector is developed using pair-wise soil property comparisons. The final classification is determined from the cross product of the weighted vector and the evaluation matrix. Two case studies are examined to validate the application of the proposed fuzzy-based method to predict soil corrosivity and the results are compared to the 10-P method. Both case studies showed that the fuzzy-based method out performed the 10-P method.Key Words: Corrosion, 10-P method, soil corrosivity, fuzzy-based method, water mains.

Exploring the Relationship between Soil Properties and Deterioration of Metallic Pipes Using Predictive Data Mining Methods

“…The five variables are described and summarized in Table 2. The data set used in this analysis was collected in 1990s from 45 locations in North American cities to study the growth of corrosion pits in cast iron pipes (Sadiq et al 2004). The summary of the data is shown in Table 3, and the corresponding scatter plot is given in Fig.…”

“…Corrosion is the most important factor that contributes to the failure of metallic water mains (Sadiq et al 2004), while other factors, such as casting technology, manufacturing defects, and environmental conditions are contributing factors that affect the structural properties of water pipes. A number of criteria have previously been proposed to assess the structural condition of a pipe, among which breakage frequency and corrosion pit depths are common ones (Kleiner and Rajani 2001).…”

“…A number of criteria have previously been proposed to assess the structural condition of a pipe, among which breakage frequency and corrosion pit depths are common ones (Kleiner and Rajani 2001). Corrosion in cast iron pipes generally takes place in the form of graphitic corrosion, where iron leaches out leaving behind the graphite matrix (Sadiq et al 2004). A corrosion pit develops, while the remaining carbon remains intact, therefore reducing the tensile strength of the pipe (Rajani et al 2000).…”

“…Instead of using a binary result to describe soil corrosivity, Sadiq et al (2004) proposed a fuzzy-based method to classify soil corrosivity into three categories: non-corrosive, moderately corrosive, and corrosive. Membership functions for each type of soil properties were defined as three continuous ordinal states.…”

Risk-Based Prioritization of Air Pollution Monitoring Using Fuzzy Synthetic Evaluation Technique

“…Such reasoning has a central importance for many emerging technologies related to engineering and applied sciences. This approach has proved very useful in medical diagnosis (Lascio et al, 2002), information technology (Lee, 1996), water quality assessment (Lu et al, 1999;Lu and Lo, 2002;Sadiq et al, 2004a), corrosion of cast iron pipes (Sadiq et al, 2004b) and in many other industrial applications (Lawry, 2001 between an uncertain quantity x and a membership function µ, which ranges between 0 and 1. A fuzzy set is an extension of the traditional set theory (in which x is either a member of set A or not) in that an x can be a member of set A with a certain degree of membership µ. Fuzzy-based techniques can help in addressing deficiencies inherent in binary logic and are useful in…”