MétaCan
Menu
Back to cohort
Record W2315082133 · doi:10.1061/9780784413142.118

Structural Design Equations for Bell and Spigot Joints in Culverts under Vehicle Load

2013· article· en· W2315082133 on OpenAlexafffund
Yu Wang, Ian D. Moore

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie University
KeywordsCulvertStiffnessStructural engineeringJoint (building)KinematicsRotation (mathematics)Shear (geology)Shear forceGeotechnical engineeringEngineeringGeologyMathematicsPhysicsGeometryClassical mechanics

Abstract

fetched live from OpenAlex

The structural design of joints in highway culverts requires evaluation of expected values of both the shear force across the joint and the joint rotation that result from vehicle loads. This paper describes new design equations that have recently been developed for estimating shear force and rotation in bell and spigot joints for both rigid and flexible culverts. The equations are exact closed form solutions based on the modeling of the pipes as elastic beams, and the Winkler soil model (where the soil stiffness is represented using a series of elastic springs). The kinematic assumptions are explained and the equations are presented. Comparisons are included between estimates of joint rotations under surface loads and rotations measured during full-scale laboratory experiments. The paper concludes with a discussion of how shear force and rotation depend on pipe diameter, pipe stiffness and burial depth.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.019
GPT teacher head0.213
Teacher spread0.194 · 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

Citations5
Published2013
Admission routes2
Has abstractyes

Explore more

Same topicGeotechnical Engineering and Underground StructuresFrench-language works237,207