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Record W2900274083 · doi:10.1115/ipc2018-78616

Study of Safe Dig Pressure Level for Rock Dents in Gas Pipelines

2018· article· en· W2900274083 on OpenAlexaff
Udayasankar Arumugam, Ming Gao, Ravi Krishnamurthy, Rick Wang, Richard Kania

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsTransCanada (Canada)
Fundersnot available
KeywordsExcavationDitchCrackingGeotechnical engineeringPipeline transportMining engineeringEngineeringInternal pressureFinite element methodRock mass classificationGeologyStructural engineeringMechanical engineeringMaterials science

Abstract

fetched live from OpenAlex

Pipelines passing through hilly-terrain potentially have numerous rock dents. Some of them require further in-ditch investigation. However, in-ditch experience revealed elastic rebounding and re-rounding due to internal pressure that could cause cracking on dent outside surface when rock is removed even after following the commonly used pressure reduction by industry. Such OD-surface cracking in rock dent could pose safety issues to excavation crew and immediate integrity threat due to gas release. A preliminary research was performed to determine the required safe dig pressure level for rock dent excavation and address if there is a gap between the common industry practice for pressure reduction. This research could assist pipeline operators with setting a safe dig pressure level for rock dent excavation. The research consists of four components. First, detail review of rock dents cracking experience during excavation has been performed and identified relevant parameters that contributed to OD-cracking. Then, performed several rock dent case studies with different dent depths, indenter sizes, internal pressures and developed criterion for OD cracking using Finite Element Analysis. Thirdly, a decision chart was developed for safe rock dent excavation and presented. Finally, full-scale denting tests with internal pressure was conducted to corroborate the safe dig pressure criterion and compared against FEA results. In this paper, all above components are presented with summary of findings and recommendations for future research.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.042
GPT teacher head0.288
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2018
Admission routes1
Has abstractyes

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