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Record W2811301502 · doi:10.1080/19386362.2018.1483812

A finite-discrete element approach for modelling polyethylene pipes subjected to axial ground movement

2018· article· en· W2811301502 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Geotechnical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsFinite element methodPolyethyleneDistortion (music)Geotechnical engineeringDiscrete element methodMaterials scienceGranular materialSoil structure interactionStructural engineeringEngineeringMechanicsComposite materialPhysics

Abstract

fetched live from OpenAlex

The response of medium-density polyethylene (MDPE) pipes subjected to ground movement is often investigated using soil-pipe interaction models that were originally developed for steel pipes. In this study, the behaviour of MDPE pipes buried in dense sand under pull-out force is investigated using a coupled finite-discrete element framework. The pipe is modelled using finite elements whereas the granular soil is modelled using discrete elements. The model is validated using experimental data and then used to investigate the response of the pipe and the surrounding soil. The response of the MDPE pipe-soil system to axial loading is found to differ significantly from that of steel pipes due to the elongation and distortion that develop in the MDPE pipes, which affect the mobilized friction forces along the pipe. This study demonstrates that caution must be exercised when using current methods in the analysis of MDPE pipes.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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