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Record W4413637725 · doi:10.14796/jwmm.c560

Comparison of Experimental Hydraulic Coefficients on Fixed and Mobile Bed Materials in Open Channel Flow

2025· article· en· W4413637725 on OpenAlexvenueno aff
Lemita Berisha Urto, Elias Gebeyehu Ayele, Otoma Orkaido Garo, Engida Amare Erigalo

Bibliographic record

VenueJournal of Water Management Modeling · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
Fundersnot available
KeywordsOpen-channel flowChannel (broadcasting)Flow (mathematics)MechanicsComputer scienceMaterials scienceGeologyPhysicsTelecommunications

Abstract

fetched live from OpenAlex

The prediction of hydraulic coefficients, which varies for different materials, is an essential criterion for designing open channels and related hydraulic structures. The main objective of this research is to compare experimental hydraulic coefficients on fixed and mobile bed materials in open channel flow. The study considered three types of bed roughness; namely steel beds, 2 mm uniform beds, and 25 mm uniform grain-sized beds in a rectangular flume model with a 1:500 and 1:200 adjustable bed slope. Manning's roughness coefficient and Chezy's equations were used to model channel bed roughness concerning the variation of flow characteristics for different bed conditions. The results showed that Manning's roughness coefficient had an inverse relationship with the discharge, flow depth, hydraulic radius, flow conveyance, and Chezy’s coefficient, but it was directly proportional to grain size. The values of mean velocity in the mobile bed along the channel are comparatively less than that of the fixed bed. The percentage change of average n value due to changes in channel slope and bed condition is slightly increased by 144.95% and 150.23% under the channel slope of 1:200, and 143.02% and 148.04% under the channel slope of 1:500. Also, the percentage change of the average C value is slightly decreased by 59.97% and 59.98% under the channel slope of 1:200, and 58.75% and 59.42% under the channel slope of 1:500 when the bed changed from fixed to mobile 2 mm and 25 mm grain sizes, respectively.

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)0.001
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 score0.676
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.298
Teacher spread0.274 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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