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Record W3125130972 · doi:10.1115/ipc2020-9384

Development of Soil Restraints for Buried Pipelines in Muskeg Soils Subjected to Lateral Ground Displacements

2020· article· en· W3125130972 on OpenAlexaff
Dharma Wijewickreme, Thushara Jayasinghe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeotechnical engineeringPipeline transportSoil waterGeologyCone penetration testEnvironmental scienceSoil science

Abstract

fetched live from OpenAlex

Abstract A systematic research program was undertaken with the objective of developing quantitative geotechnical parameters to support soil-pipe interaction assessment for buried pipelines in muskeg. For this purpose, a field geotechnical investigation program comprising cone penetration testing (SCPT) with shear wave velocity (Vs) measurements, electronic field vane shear testing (eVST), full-flow ball penetration testing (BPT), and pressuremeter testing (PMT), along with fixed-piston tube soil sampling was undertaken in a muskeg soil terrain. The data from field testing were initially interpreted to obtain typical stiffness and strength parameters for the subject soils. These parameters were then used to numerically simulate pressuremeter tests and the results were compared with those obtained from field pressuremeter testing; the intent was to calibrate a suitable constitutive model to represent the muskeg soil mass. These ascalibrated constitutive model was then applied on numerical models developed to simulate buried pipelines in muskeg soil subject to relative lateral ground movements. The work is aimed at developing a framework to generate soil restraint versus relative ground displacement relations (“soil springs”) to assess soil-pipe interaction of pipelines buried in muskeg soils. Initial results from the research are presented herein, with a comparison made between soil springs developed from numerical analyses and those generated from current practice guidelines.

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)0.000
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.233
Teacher spread0.215 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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