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- W3124153475 abstract "Abstract An enhanced corrosion assessment model has been developed by TC Energy. The new model is called the “Plausible Profiles Model for Corrosion Assessment” or “Psqr” for short and is described in three IPC 2020 papers1,2,3. The Psqr model uses a probabilistic approach for creating a number of plausible profiles along a corroded area. The predicted failure pressure for each plausible profile is calculated using RSTRENG, resulting in a probabilistic distribution of predicted failure pressures. The predicted failure pressure for the corroded area is taken to be the lower 5th percentile value of the distribution. TC Energy requested that PRCI sponsor an independent review of the Psqr model by subject matter experts (SMEs). The PRCI Corrosion Technical Committee and TC Energy jointly selected a team of SMEs to conduct the review. The team was comprised of the following individuals: • Maher Nessim — C-FER Technologies • Ming Gao — Blade Energy Partners • Ravi Krishnamurthy — Blade Energy Partners • Phil Hopkins — Independent Consultant • Andrew Cosham — Ninth Planet Engineering • Michael Rosenfeld — RSI Pipeline Solutions • Bruce Nestleroth — Kiefner and Associates, Inc. • John Kiefner — RSI Pipeline Solutions This paper describes the work carried out by the SMEs and presents their findings and conclusions. Basically, they found that the model is more accurate and exhibits less scatter than existing models such as RSTRENG, B31G, and Modified B31G4. They recommended that the Psqr Model be implemented in conjunction with a high-quality corrosion management plan such as that outlined in TC Energy’s technical report5, and they recommended specific minimum Psqr-predicted failure stress levels for use on pipelines being operated at maximum stress levels ranging from 40% of SMYS to 80% of SMYS." @default.
- W3124153475 created "2021-02-01" @default.
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- W3124153475 date "2020-09-28" @default.
- W3124153475 modified "2023-09-25" @default.
- W3124153475 title "Peer Review of the Plausible Profiles Corrosion Assessment Model" @default.
- W3124153475 doi "https://doi.org/10.1115/ipc2020-9254" @default.
- W3124153475 hasPublicationYear "2020" @default.
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