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Modeling Pipeline Metal Loss Defects at Tool Speed

[+] Author Affiliations
Matthew Romney

T. D. Williamson, Salt Lake City, UT

Adrian Belanger

T. D. Williamson, Houston, TX

Paper No. IPC2018-78014, pp. V001T03A001; 8 pages
doi:10.1115/IPC2018-78014
From:
  • 2018 12th International Pipeline Conference
  • Volume 1: Pipeline and Facilities Integrity
  • Calgary, Alberta, Canada, September 24–28, 2018
  • Conference Sponsors: Pipeline Division
  • ISBN: 978-0-7918-5186-9
  • Copyright © 2018 by ASME

abstract

Accurate defect sizing is crucial for maintaining effective pipeline safety and operation. Under growing pressure from local, national and world organizations, pipeline operators demand improved magnetic flux leakage (MFL) metal-loss sizing accuracy and classification from in-line inspection (ILI) tools.

The axial MFL field response in pipeline steel near a metal-loss defect is a very complex phenomenon. Although critical for proper sizing model development, the effects of tool speed due to product flow is very difficult to model during finite element analysis (FEA) and therefore is often overlooked. However, understanding the dynamic MFL response is crucial for proper ILI tool design and the development of accurate defect sizing algorithms.

T.D. Williamson (TDW) utilizes dynamic computer simulation modeling, paired with laboratory testing, to develop the complex parametric relationships between metal loss geometry, pipeline material and ILI tool speed. The blend of simulation and physical test results allow for TDW to iterate more quickly across multiple physics variables with simulation models, while maintaining a firm footing in reality with physical test validation. Accurately simulating magnetic field responses of metal loss under dynamic conditions produces the data necessary to identify optimal magnetizer design, including optimizing sensor spacing and placement for metal-loss defect sizing and characterization.

This paper will provide an overview of advances in the use of computer simulation modeling for predicting dynamic flux leakage field response. Besides increasing accuracy, results from this work will extend specifications beyond optimal speed ranges and provide the basis for general corrosion profilometry predictions from decomposition of the full MFL signal.

Copyright © 2018 by ASME
Topics: Metals , Modeling , Pipelines

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