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Record W4388414442 · doi:10.1080/00221686.2023.2259859

Experimental investigation of the hydrodynamic field around a half-cone woody debris jam on a bridge pier

2023· article· en· W4388414442 on OpenAlexafffund
Wenjun Zhang, Colin D. Rennie, Ioan Nistor

Bibliographic record

VenueJournal of Hydraulic Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilUniversity of Ottawa
KeywordsDebrisPierGeologyGeotechnical engineeringWakeDebris flowDragMechanicsStructural engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

A debris jam causes extra load and associated scour on a bridge pier, and this significantly affects the safety of the bridge. Laboratory experiments were conducted to investigate the flow field around half-cone shaped debris jams of equal size, following the geometry in previous field studies, but with different surface roughness. The debris jams were assembled using dowels or by 3D printing. The results indicate three zones were observed behind the debris jam: the wake dead zone, high shear transition zone, and accelerated high-speed zone. A debris jam enlarges the dead zone while Reynolds shear stress was greatest in the transition zone for all debris jam cases. Additionally, the drag coefficient of debris jams built by dowels was greater compared with the 3D-printed debris jam, attributed to the debris jam roughness. In summary, debris jams form the wake dead zone behind the pier, increase downward flow in front of the pier, and enhance flow acceleration around the pier, highlighting the potential hazards to bridge safety.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.050
GPT teacher head0.331
Teacher spread0.281 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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