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Record W4360605086 · doi:10.1139/cjce-2022-0353

Effect of ramp slope on the efficiency of hump weirs in free flow condition

2023· article· en· W4360605086 on OpenAlexafffundvenue
Amir H. Azimi, Arash Ahmadi, Abul B. M. Baki

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDischarge coefficientHead (geology)WeirFlow (mathematics)Flow conditionsMechanicsWater dischargeHydraulic headGeotechnical engineeringEnvironmental scienceUpstream (networking)Volumetric flow rateGeologyEngineeringNozzlePhysicsGeomorphology

Abstract

fetched live from OpenAlex

A series of numerical simulations was performed to study the discharge capacity of symmetrical hump weirs in free flow condition. A wide range of ramp slopes was selected from 1 V:1 H to 1 V:5 H and the effects of flow discharge and ramp slope on variations of discharge coefficient were investigated. The variations of upstream water head with discharge indicated the existence of two distinct flow regimes on free flow over symmetrical hump weirs. It was found that the discharge coefficient increased with increasing the upstream water head until the maximum discharge coefficient was achieved. Further increase of water head caused a reduction in discharge coefficient and the flow regime became inefficient. The proposed models for prediction of discharge characteristics of sharp-crested weirs with an upstream and (or) downstream ramp(s) from the literature were also compared with the discharge capacity of sharp-crested weirs to study the effects of ramp slope. It was found that the available head–discharge models are acceptable for hump weirs with small ramp length and more accurate prediction models are required for symmetrical hump weirs with larger ramps. The boundary curve to determine the optimum performance in symmetrical hump weirs was introduced, and the head–discharge models for both efficient and inefficient discharge conditions were proposed.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.004
GPT teacher head0.181
Teacher spread0.177 · 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

Citations1
Published2023
Admission routes3
Has abstractyes

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