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Measured Responses of a Corrugated Steel Ellipse Culvert at Different Cover Depths

2020· article· en· W3083871456 on OpenAlexaff
Oliver Kearns, Ian D. Moore, Neil A. Hoult

Bibliographic record

VenueJournal of Bridge Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsQueen's University
Fundersnot available
KeywordsCulvertBending momentStructural engineeringThrustBendingGeotechnical engineeringMoment (physics)Flexural strengthYield (engineering)EngineeringGeologyMaterials scienceComposite materialPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

Typical design and installation methods for corrugated steel culverts involve consideration of a minimum burial depth and most current North American design codes consider failure only due to excessive circumferential force in the conduit walls (i.e., hoop thrust). However, recent studies have shown that the bending moment is often the more dominant behavior for corrugated steel culverts at shallow cover. To address this issue, an elliptical corrugated steel culvert was tested under simulated vehicle loading at depths ranging from 0.1 to 1.2 m. The results show that, under a wheel pair load, a peak negative bending moment, and thrust, force is consistently developed at the crown with positive bending moments adjacent to the crown and near the shoulders. When the flexural and circumferential force results are extrapolated to the yield point and compared, the bending moment values are up to five times larger than the yield limit while thrust values are only 60% of the limit. The test results suggest that bending moments should be considered during the design and installation of corrugated steel culverts at shallow cover.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.203
Teacher spread0.186 · 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 designObservational
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

Citations22
Published2020
Admission routes1
Has abstractyes

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