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Record W2805997178 · doi:10.1061/9780784481578.070

Experimental Investigation of Granular Bulk Density Effect on Bridge Local Scour under Clear-Water Conditions

2018· article· en· W2805997178 on OpenAlexaboutno aff
Junhong Li, Junliang Tao

Bibliographic record

VenueIFCEE 2018 · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)Geotechnical engineeringBridge scourGeologyStructural engineeringPierEngineering

Abstract

fetched live from OpenAlex

The effect of granular bulk density on local scour around an oblong pier under clear-water conditions is studied. A total of four open channel flume tests were conducted, in which the sediment beds were prepared at different relative states of compaction. Uniform Ottawa sand was used for all cases. Flow conditions, i.e., flow velocity and depth, were maintained the same for all cases to isolate the bulk density effect. Time evolution of the maximum scour depth and the scoured bed morphology were compared among all cases. For tests on sediment beds of the lowest and highest density, three miniature pressure transducers were installed at various depths within the bed upstream of pier nose to monitor the pore pressure response. Experimental results indicate that the erosive resistance of the sand bed is a slightly decreasing function of bulk density. The possible underlying mechanism, responsible for such different scour behaviors between test cases, is also discussed.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.013
GPT teacher head0.246
Teacher spread0.233 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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