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Record W3045415361 · doi:10.1139/cjce-2020-0043

Structural evaluation of invert-cut circular and arch shape corrugated steel pipes through laboratory testing

2020· article· en· W3045415361 on OpenAlexvenueno aff
Amin Darabnoush Tehrani, Zahra Kohankar Kouchesfehani, Hiramani Raj Chimauriya, Samrat Raut, Mohammad Najafi, Xinbao Yu

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsCulvertArchStructural engineeringEmbedmentStiffnessGeotechnical engineeringEngineeringSpan (engineering)

Abstract

fetched live from OpenAlex

Culverts are important components of highway infrastructure. They are structurally designed to support earth and live traffic loads. Corrugated steel pipes (CSPs) are widely used as culverts in North America in different geometries. However, due to the corrosive nature of the stormwater passing through the culverts, it is common to find CSPs with partially or entirely lost inverts. Dependent on site, depth of cover and embedment conditions, invert deterioration would not necessarily result in culvert failure. This paper presents the results of a laboratory testing campaign that evaluates the structural capacity of two circular CSPs and their equivalent arch CSP through the application of a vertical static loading. The circular pipe samples had a length of 6 ft (1.82 m) and a diameter of 60 in. (1.52 m). The same length arch pipe sample had a span of 71 in. (1.8 m) and a rise of 47 in. (1.19 m). The invert of the arch and one of the circular CSPs were cut to simulate heavily corroded culverts in service. The pipe samples were embedded under two feet (0.6 m) of cover using one foot (0.3 m) of sand and one foot (0.3 m) of coarse aggregates on top, simulating a base course layer of pavement. The results of testing showed that the invert-cut circular CSP was highly dependent on its ring stiffness. While, the invert-cut arch CSP took advantage of its arch geometry and was able to resist the applied load without significant loss in the sample pipe’s horizontal dimension.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.028
GPT teacher head0.209
Teacher spread0.181 · 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

Citations18
Published2020
Admission routes1
Has abstractyes

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