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Record W4402061402 · doi:10.1061/9780784485569.052

Design of a New Full-Scale Vertical Ground Deformation Facility for Testing Buried Pipelines

2024· article· en· W4402061402 on OpenAlexaff
J. Matymish, Ian D. Moore, Neil A. Hoult, Joshua E. Woods

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsQueen's University
Fundersnot available
KeywordsPipeline transportDeformation (meteorology)Scale (ratio)GeologyEngineeringMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Current full-scale experimental practices for pipes subjected to ground movements are limited to simple, abrupt ground movement profiles, such as normal faults; however, more complicated ground movements from earthworks and ground subsidence occur in the field. A new facility is being developed at Queen’s University to simulate these more complex ground movements. The facility is the next generation of the laboratory’s normal fault simulator (the “Split Box”) and consists of a full-scale soil chamber with a stationary floor and three independent moving floor sections. Hydraulic actuators will be installed at both ends of the facility to permit investigations of relative axial ground movement and upheaval buckling. These new features will facilitate improved understanding of soil–pipe interaction problems. The conceptual design of the facility is discussed and ABAQUS soil modelling is used to verify the feasibility of creating a versatile set of vertical ground movement profiles at depths practical within a laboratory setting. The novel techniques that will be implemented in the new facility form an important next step in modeling and understanding the response of buried pipelines subjected to differential ground movement and are expected to aid in the improvement of pipeline design and assessment.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.029
GPT teacher head0.233
Teacher spread0.204 · 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
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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