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Record W4379647068 · doi:10.1061/jhend8.hyeng-13245

Empirical Determination of Free Alternate Bar Length

2023· article· en· W4379647068 on OpenAlexaff
Yunshuo Cheng, Ana Maria Ferreira da Silva

Bibliographic record

VenueJournal of Hydraulic Engineering · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsQueen's University
Fundersnot available
KeywordsBar (unit)Range (aeronautics)Stability (learning theory)Dispersion (optics)MathematicsBasis (linear algebra)Field (mathematics)STREAMSPhysicsComputer scienceGeometryEngineeringMeteorologyOptics

Abstract

fetched live from OpenAlex

A new empirical equation for free alternate bar length at the fully developed state is introduced. The equation is developed on the basis of dimensional analysis and all readily available data. A special effort is also made to align the formulation with findings from existing theoretical and numerical analyses of the development of alternate bars, and more specifically those resulting from a stability analysis of the phenomenon. When applied to the existing laboratory data, the equation results in significantly less dispersion around the best agreement line than that associated with previous empirical equations, yielding 70% of the data within the 20% error range, against 47% for previous equations. It is shown that previous equations perform notoriously poorly in the case of fully rough subcritical flows and all transitionally rough flows, with the present equation addressing this matter. When applied to field cases, the present equation yielded realistic values of bar length, including for large sand streams with high or very high values of relative depth (e.g., the Tagus and Mississippi Rivers).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.295

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.244
Teacher spread0.232 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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