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Record W2767022120 · doi:10.1115/1.4038224

Electrochemical Corrosion Finite Element Analysis and Burst Pressure Prediction of Externally Corroded Underground Gas Transmission Pipelines

2017· article· en· W2767022120 on OpenAlexaff
Ibrahim M. Gadala, Magd Abdel Wahab, Akram Alfantazi

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2017
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCorrosionCathodic protectionMaterials scienceFinite element methodPipeline transportStress (linguistics)StiffnessCoatingNonlinear systemStructural engineeringComposite materialMetallurgyElectrochemistryElectrodeChemistryEngineering

Abstract

fetched live from OpenAlex

An integrative numerical simulation approach for pipeline integrity analysis is presented in this work, combining a corrosion model, which is the main focus of this paper, with a complementary structural nonlinear stress analysis, using the finite element method (FEM). Potential distributions in the trapped water existing beneath pipeline coating disbondments are modeled in conjunction with reaction kinetics on the corroding exposed steel surface using a moving boundary mesh. Temperature dependencies (25 °C and 50 °C) of reaction kinetics do not greatly affect final corrosion defect geometries after 3-yr simulation periods. Conversely, cathodic protection (CP) levels and pH dependencies within the near-neutral pH range (6.7–8.5) strongly govern depth profiles caused by corrosion, reaching a maximum of ∼3 mm into the pipeline wall. A 0.25 V amplification of CP potential combined with a 0.5 mm widening in disbondment opening size reduces defect penetration by almost 30%. Resulting corrosion defect geometries are used for stress examinations and burst pressure evaluations. Furthermore, nonlinear elastic–plastic stress analysis is carried out using shell elements in order to predict the burst pressure of corroded pipes. Corrosion is modeled by reducing the stiffness of a damaged element that has the dimensions of the defect. The predicted burst pressures are in good agreement with those obtained using an experimental-based formula.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.262
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2017
Admission routes1
Has abstractyes

Explore more

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