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Calculating Local Force of Corrugated Steel Culvert Buried at Shallow Cover Depth Using a Thrust Modification Factor

2022· article· en· W4307644217 on OpenAlexaff
Elham Nakhostin, Shawn Kenny, S. Sivathayalan

Bibliographic record

VenueJournal of Bridge Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsCarleton University
Fundersnot available
KeywordsCulvertThrustStructural engineeringLoad factorGeotechnical engineeringMoment (physics)GeologyEngineeringEnvironmental sciencePhysicsMechanical engineering

Abstract

fetched live from OpenAlex

Current practice only considers the net (average) thrust for in-service engineering assessment of buried corrugated steel culverts (CSCs). In this study, numerical simulations have demonstrated, for shallow cover depth conditions (H/D < 2), the importance of local peak thrust and combined load effects (i.e., thrust and moment), which occur between the CSC shoulder and crown locations. These observations are supported by independent, third-party, full-scale, physical modeling studies. A global sensitivity analysis was conducted to identify the influential variables, assess the significance of any interaction, and estimate the influence on the predicted response. Based on this analysis, a limit state function for combined load effects and modification factor to account for the local peak thrust force was developed. The reliability index for the proposed coefficients was also established.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.230
Teacher spread0.208 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

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