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Record W2161454681 · doi:10.3141/2201-07

Ultimate Limit State of Deep-Corrugated Large-Span Box Culvert

2010· article· en· W2161454681 on OpenAlexaffabout
R.W.I. Brachman, Ian D. Moore, A. C. Mak

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2010
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsBGC Engineering (Canada)Queen's University
Fundersnot available
KeywordsCulvertStructural engineeringLimit state designSpan (engineering)AxleUltimate loadGeotechnical engineeringEngineeringStructural loadFinite element method

Abstract

fetched live from OpenAlex

Limit state design requires independent assessment of both load and resistance. Although much is known about the live and dead loads that may act on box culverts, there is no known measurement of the resistance (or capacity) at the ultimate limit state. The objective of this study is to present results from a full-scale experiment conducted on a buried, deep-corrugated, large-span box culvert under controlled laboratory conditions—the first conducted to its ultimate limit state. The box culvert had a 2.4-m rise and 10-m span (7.9 × 32.8 ft) and was fabricated from steel plate 6 mm thick with corrugations 150 mm deep at a 400-mm pitch (0.24 × 6 × 16 in.). The box culvert was backfilled to a minimum cover depth of 0.45 m (1.5 ft) with densely compacted well-graded sand and gravel. Tandem-axle loading was then applied by an actuator until an ultimate limit state was attained. The ultimate limit state of the box culvert involved the formation of plastic hinges at the crown and shoulders at a total applied force of 1,100 kN (250 kips). The force required to reach the ultimate limit state was 1.8 times larger than the factored design tandem-axle load from the AASHTO bridge design specifications. Similarly, the factored resistance at the ultimate limit state was 1.7 times larger than the factored CL-625-ONT tandem-axle load from the Canadian highway bridge design code.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
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 head0.026
GPT teacher head0.309
Teacher spread0.284 · 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.

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

Citations34
Published2010
Admission routes2
Has abstractyes

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