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Observations on Flow around Bridge Abutment

2000· article· en· W2147132250 on OpenAlexafffund
Ferdous Ahmed, N. Rajaratnam

Bibliographic record

VenueJournal of Engineering Mechanics · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPierAbutmentGeologyFlow (mathematics)Geotechnical engineeringTurbulenceShear stressBoundary layerMechanicsSimilarity (geometry)Structural engineeringEngineeringPhysicsComputer science

Abstract

fetched live from OpenAlex

Results are presented from an experimental investigation into the skewed three-dimensional flow around a bridge abutment. Velocity profiles on the plane of symmetry matched the standard log-law only near the bed and revealed a rather uniform flow in the upper layer. The bed shear stress was found to amplify nearly 3.63 times near the nose of the abutment. The flow was deflected least at the midwater depth, exceeded slightly by the upper flow and substantially by the lower flow. The flow was also analyzed using the theories of three-dimensional turbulent boundary layers. None of the crossflow models matched the data. The performance of near-wall similarity models was also poor. However, strong evidence of near-wall similarity was found very near to the bed. Compared to the bridge pier flow, greater skewing was found in abutment flow, especially in the downstream region, showing the limitations of treating the abutment as a half-pier.

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)0.000
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
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 head0.015
GPT teacher head0.201
Teacher spread0.185 · 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

Citations71
Published2000
Admission routes2
Has abstractyes

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