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Record W4405362418 · doi:10.1115/ipc2024-121381

Uplift Mitigation Strategies for Pipeline Overbends

2024· article· en· W4405362418 on OpenAlexaff
Ryan Phillips, M. Martens, J. Barrett, Gerry Piercey

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsCentre For Cold Ocean Resources Engineering
Fundersnot available
KeywordsPipeline (software)Computer scienceGeologyProgramming language

Abstract

fetched live from OpenAlex

Abstract Pipeline upheaval buckling due to insufficient vertical restraint and ratcheting caused by cyclic loading are especially challenging issues, with each likely to occur at overbends. A primary factor contributing to the uplift resistance available to counteract upheaval buckling is the strength of, and the ability to mobilize the overlying soil. Overbends have the potential to require additional uplift resistance, over and above that provided by the native backfill, to resist upheaval buckling. This buckling has primarily been mitigated by relying on increased soil cover or through the use of screw anchors in competent soils. These mitigations have drawbacks, as greater than required burial depths add to construction time and cost, while screw anchors can increase localized stresses on the pipeline. To assess currently available uplift resistances and evaluate the effects of various potential mitigation measures, a series of laboratory uplift tests using scaled pipe sections and granular backfills were completed. To address insufficient uplift resistance, a series of prototype mitigation measures were chosen for proof of concept testing. The design of each measure focused on increasing the peak uplift resistance and maintaining a residual resistance closer to the peak, without significantly increasing cover depths or stresses applied to the pipeline. Three of the concepts tested, a structural cap layer, pipe stirrups and a rigid open saddle each widened the soil column mobilized during uplift, increasing the peak resistances achieved in scaled testing, while also maintaining the integrity of the soil block at larger displacements, thus reducing the decay often seen in residual resistances. These concepts showed promise and were advanced from prototype to a field deployable design.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.223
Teacher spread0.217 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2024
Admission routes1
Has abstractyes

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