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Record W2052467637 · doi:10.1115/ipc2010-31353

Parametric Study of Sleeve Repair on Wrinkled Energy Pipelines

2010· article· en· W2052467637 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2010 8th International Pipeline Conference, Volume 1 · 2010
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsPetroleum Technology Alliance CanadaUniversity of Alberta
Fundersnot available
KeywordsParametric statisticsWrinkleStructural engineeringFinite element methodPipeline transportPipeline (software)Work (physics)Materials scienceEngineeringMechanical engineeringComposite materialMathematics

Abstract

fetched live from OpenAlex

Field experience showed that repairing wrinkles developed on energy pipelines using steel sleeves is an efficient and cost effective method. Based on the previous successful numerical simulations of a field wrinkle sleeve repair work, a parametric study was conducted by using Finite Element (FE) method to further investigate the effectiveness of the sleeve repair technique. The FE package ABAQUS 6.4 was utilized in conducting the parametric study. The parameters studied include the length, the thickness, and the material properties of the sleeve, and the thickness of the collar, which is used to fit between the wrinkled pipe and the repairing sleeve. The range of the parameters studied covers the most commonly used typical values in the pipeline industry. Two phases were used in carrying out the parametric study. In Phase I, the parameter that plays the most important role in determining the behavior of the wrinkle sleeve repair system (WSRS) was studied. It is found this parameter is the length of the repairing sleeve. Brief discussion was given regarding the way this parameter affects the behavior of the pipe using the WSRS. In Phase II, based on the results from the Phase I study, the effects of other parameters were investigated through a series of FE analyses. Conclusions were drawn and recommendations for future wrinkle sleeve repair work were given based on the results of the parametric study.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.244
Teacher spread0.228 · 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