Abstract

The main problems discussed in the article concern the analysis of the phenomenon of stray currents generated by electric D.C. traction currents. These currents flow in the ground and, when they encounter an underground metal structure, can lead to the acceleration of electrochemical corrosion. There is a stochastic phenomenon that depends on many factors such as the position of the traction vehicle along the route or the current drawn by it from the traction network. The presented research concerns the use of probabilistic methods to analyze this phenomenon. The proposed algorithm allows determining the occurrence of electrochemical-pipeline corrosion risk for geometrically complex traction-pipeline systems, including many random variables and corrosion phenomena. The non-deterministic solution to such an interdisciplinary problem is an element of novelty.

Highlights

  • Stray currents flowing into the ground from D.C. electric traction return circuits are still the greatest corrosion risk for steel objects operating underground, such as pipelines or tanks.Despite that, as a result of standardization activities (e.g., [1,2]), several modern solutions have been introduced to everyday technical practices, such as requirements concerning the limiting of stray current leakage from rails to the ground or the protection of metal structures against external electric interactions

  • To sum up, it is worth remarking that, in the study, the pipeline response to D.C. stray currents as a function of time has not been analysed. This approach is usually used in the analysis of corrosion risks caused by stray currents, and is extensively described in the literature. In contrast to this approach, a simulation method assuming random character of stray currents, using appropriate electrical equivalent models of earth return circuits involved in combination with the Monte Carlo procedure and taking into account electrochemical phenomena occurring at the metal–soil electrolyte interface has been proposed

  • The developed method allows determining the probability of occurrence of anode zones along the pipeline laid near the direct current electrical traction, assuming that the position of the electric locomotives and the current drawn by the locomotives are random variables

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Summary

Introduction

Stray currents flowing into the ground from D.C. electric traction return circuits (rail and tram) are still the greatest corrosion risk for steel objects operating underground, such as pipelines or tanks. This approach is usually used in the analysis of corrosion risks caused by stray currents, and is extensively described in the literature In contrast to this approach, a simulation method assuming random character of stray currents, using appropriate electrical equivalent models of earth return circuits involved (railway rails and pipeline) in combination with the Monte Carlo procedure and taking into account electrochemical phenomena occurring at the metal–soil electrolyte interface has been proposed. The developed method allows determining the probability of occurrence of anode zones (at risk of corrosion) along the pipeline laid near the direct current electrical traction, assuming that the position of the electric locomotives and the current drawn by the locomotives are random variables This is an interdisciplinary problem at the interface between electrical engineering (earth return circuits theory, electrical traction, and non-deterministic network analysis) and electrochemistry (stray current corrosion and kinetics of electrode processes: Butler-Volmer equation). The solution to such an interdisciplinary problem is an element of novelty

Electric Potential of Rail Modeled as a Circuit with Distributed Parameters
Electric Potential of Rail Modeled as Circuit with Lumped Parameters
General Considerations
Pipeline as Circuit with Distributed Parameters
Lumped-Parameter Model of Energized Pipeline by Controlled-Voltage Source
Incorporating Electrode Kinetics
Simulation Model Incorporating Monte Carlo Procedure
Calculation Examples
Result Comparison
Findings
Conclusions
Full Text
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