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Record W2740771823 · doi:10.5006/c2017-09592

Case Study: Engineered Polyamide 12 (PA12) Pipeline Liner for Management of Sour Gas Corrosion at Elevated Temperatures

2017· article· en· W2740771823 on OpenAlexaboutno aff
J. F. Mason, Akshay M Ponda, Daniel Demicoli

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsnot available
Fundersnot available
KeywordsSour gasPolyamideCorrosionMaterials sciencePipeline (software)Composite materialMetallurgyWaste managementNatural gasEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Field-inserted thermoplastic liners are often the preferred corrosion management option in crude oil and gas gathering lines in cases where water, salt, and acid gases create difficult corrosion management challenges. HDPE has been the most used material for plastic liners for a long time but performance limitations of conventional HDPE liners in higher temperature applications as well as in sour, multiphase, crude gathering lines are well known. A polyamide 12 (PA12) material has been specifically engineered for use in a much broader range of conditions with longer design lifetimes. After extensive laboratory testing and analysis including chemical resistance testing, mechanical durability studies, and installation method compatibility testing, a significant project was developed to install PA12 in the Lone Pine Creek field near Calgary, Alberta, Canada. The sour, multiphase, pipeline normally operates at 45° C with H2S concentration of 12.5 mole percent. The material qualification program is discussed, followed by the liner design and installation process. Performance of the liner in service are described as well as the results of inspection of test coupons placed in the flow stream for a period of one year.

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)0.000
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 score0.007
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

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

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 head0.036
GPT teacher head0.300
Teacher spread0.263 · 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

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