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Record W3083431401 · doi:10.1139/cgj-2020-0049

Deformation capacity of buried hybrid-segmented pipelines under longitudinal permanent ground deformation

2020· article· en· W3083431401 on OpenAlexvenueno aff
Gersena Banushi, Brad P. Wham

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsPipeline transportPipeline (software)Joint (building)Deformation (meteorology)Structural engineeringDisplacement (psychology)Geotechnical engineeringNonlinear systemGeologyEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Innovative hybrid-segmented pipeline systems are being used more frequently in practice to improve the performance of water distribution pipelines subjected to permanent ground deformation (PGD), such as seismic-induced landslides, soil lateral spreading, and fault rupture. These systems employ joints equipped with anti-pull-out restraints, providing the ability to displace axially before locking up and behaving as a continuous pipeline. To assess the seismic response of hazard-resistant pipeline systems equipped with enlarged joint restraints to longitudinal PGD, this study develops numerical and semi-analytical models considering the nonlinear properties of the system, calibrated from large-scale test data. The deformation capacities of two hybrid-segmented pipelines are investigated: (i) hazard-resilient ductile iron (DI) pipe and (ii) oriented polyvinylchloride (PVCO) pipe with joint restraints capable of axial deformation. The numerical analysis demonstrates that, for the conditions investigated, the maximum elongation capacity of the analyzed DI pipe system is greater than that of the PVCO pipeline. The implemented semi-analytical approach revealed that the pipeline performance improves strongly by increasing the allowable joint displacement. Comparison of the numerical results with analytical solutions reported in recent research publications showed excellent agreement between the two approaches, highlighting the importance of assigning appropriate axial friction parameters for these systems.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.888

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 science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.200
Teacher spread0.183 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations23
Published2020
Admission routes1
Has abstractyes

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