Underground Corrosion Model of Steel Pipelines Using In Situ Parameters of Soil

Author:

Mohd Tahir Siti Nor Fariza Mior1,Yahaya Nordin1,Md Noor Norhazilan1,Kar Sing Lim2,Abdul Rahman Azlan1

Affiliation:

1. Faculty of Civil Engineering, Universiti Teknologi Malaysia, UTM Skudai, Johor 81310, Malaysia e-mail:

2. Faculty of Civil Engineering and Earth Resources, Universiti Malaysia Pahang, Lebuhraya Tun Razak, Gambang, Kuantan, Pahang 26300, Malaysia e-mail:

Abstract

A simple yet practical model to estimate the time dependence of metal loss (ML) in underground pipelines has been developed considering the in situ soil parameters. These parameters are soil resistivity, pH, moisture content, chloride content, and salinity. The time dependence of the ML was modeled as Pmax = ktn, where t is the time exposure, k is ML constant, and n is the corrosion growth pattern. The results of ML and in situ parameters were analyzed using statistical methods such as data screening, linear correlation analysis, principal component analysis, and multiple linear regressions. The best model revealed that k is principally influenced by ressistivity, and n appears to be correlated with chloride content. Model optimization was carried out by introducing several observation criteria, namely, water access, soil color, and soil texture. The addition of these factors has improved the initial accuracy of model to an R2 score of 0.960. As a conclusion, the developed model can provide immediate assessment of corrosion growth experienced by underground structures.

Publisher

ASME International

Subject

Mechanical Engineering,Mechanics of Materials,Safety, Risk, Reliability and Quality

Reference24 articles.

1. Cyclic Deformation Behavior and Buckling of Pipeline With Local Metal Loss in Response to Axial Seismic Loading;ASME J. Pressure Vessel Technol.,2013

2. Relationship Between Soil Properties and Corrosion of Carbon Steel;J. Appl. Sci. Res.,2012

3. An Efficient Methodology for the Reliability Analysis of Corroding Pipelines;ASME J. Pressure Vessel Technol.,2014

4. Deterministic Prediction of Corroding Pipeline Remaining Strength in Marine Environment Using DNV RP-F101 (Part A);J. Sustainability Sci. Manage.,2011

5. Time-Dependent Corrosion Growth Modeling Using Multiple In-Line Inspection Data;ASME J. Pressure Vessel Technol.,2014

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