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Record W2106823080 · doi:10.1139/l08-095

Prediction of the lateral flow regime and critical depth in compound open channels

2009· article· en· W2106823080 on OpenAlexvenueno aff
Esmaeil Kordi, Seyed Ali Ayyoubzadeh, Morteza Ahmadi, Abdolreza Zahiri

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
FundersUniversity of Mazandaran
KeywordsSupercritical flowEnergy–depth relationship in a rectangular channelOpen-channel flowFlow (mathematics)MechanicsChannel (broadcasting)Supercritical fluidCoherence (philosophical gambling strategy)Momentum (technical analysis)Cross section (physics)Energy (signal processing)GeologyStatistical physicsMathematicsThermodynamicsPhysicsComputer scienceStatisticsChézy formulaTelecommunications

Abstract

fetched live from OpenAlex

In this study, the common critical depth calculation in compound channels has been modified considering the effect of momentum transfer between the interface of a main channel and its floodplains. In noncorrected specific energy curves of a given slope, the flow is not necessarily entirely sub- or supercritical as it is in a single cross section and there is a possibility of both flow regimes at a certain stage, called the lateral mixed flow regimes, which makes the application of specific energy equation to determine the critical depth and transitional zone calculations questionable. In the present research, the flow distribution in a main channel and floodplains has been corrected by combining the corrected hydraulic flow in compound cross sections using the coherence method. The specific energy has been subsequently modified in the subsections. The results seem satisfactory when compared with the results based on the available laboratory data.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.012
GPT teacher head0.199
Teacher spread0.187 · 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

Citations10
Published2009
Admission routes1
Has abstractyes

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