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Record W2534840609 · doi:10.1115/ipc2000-142

Pipeline Maintenance in Geotechnically Unstable Areas: A Case Study

2000· article· en· W2534840609 on OpenAlexaboutno aff
Michelle L. Sorensen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringMonte Carlo methodPipeline transportEnvironmental sciencePipeline (software)Finite element methodResidualEngineeringStructural engineeringEnvironmental engineeringComputer scienceStatisticsMathematics

Abstract

fetched live from OpenAlex

The 22″ Alberta Oilsands Pipeline transports synthetic crude oil from Syncrude Canada Limited in Fort McMurray to Edmonton, Alberta. The pipeline crosses the House River approximately 100 kilometers south of Fort McMurray. The slope has been monitored since 1991 by three slope indicators. A finite element stress analysis indicated that total ground movement since installation in 1977 could correspond to pipeline compressive strains in excess of 0.32%, a level of risk unacceptable to the pipeline owner. A probability-based model was developed to determine cost and benefit of risk mitigation options. Parameters such as soil movement and pipe strain were input as probability distributions. The mitigation options included: reduce slope instability; reduce pipe stress; reduce pipe-to-soil interaction; implement long term monitoring; determine current pipe strain level (to decrease data uncertainty); do nothing. A Monte Carlo simulation was used to establish probability of failure and probable cost distributions for each option. The results were presented as a combined cost of failure and mitigation over 10 years. The analysis indicated that the optimum solution was to remove the existing soil traction loading on the pipe and mitigate long-term slope movement. The decision was made to relieve the pipe strain by excavating. Current pipe strain was measured in situ using residual strain measurement. Long term strain gauges were installed. Slope mitigation was deferred until the strain gauges indicate total pipeline strain levels approaching 0.32%.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0020.000
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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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 designCase report
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

Citations0
Published2000
Admission routes1
Has abstractyes

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