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Record W2018997563 · doi:10.1680/wama.2012.165.3.153

Direct solutions for design of grass-lined channels

2012· article· en· W2018997563 on OpenAlexaff
Said M. Easa, Ali R. Vatankhah

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Water Management · 2012
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDimensionless quantityFlow (mathematics)Channel (broadcasting)Range (aeronautics)RADIUSOpen-channel flowMathematicsProcess (computing)MechanicsComputer scienceGeometryEngineeringPhysics

Abstract

fetched live from OpenAlex

For grass-lined channels, the Manning roughness coefficient varies with the hydraulic radius and the functional relationship is highly non-linear. For this reason, a trial procedure is required in the traditional design process to solve the Manning formula to determine the bottom width and flow depth of the channel cross-section. To eliminate the trial procedure, direct graphical solutions have been developed for side slope z = 2. This paper presents direct graphical and analytical solutions for bottom width and flow depth for any value of side slope in the practical range of z = 2–8. The solutions are based on new dimensionless forms of the Manning formula. The graphical and analytical solutions for bottom width and flow depth are either exact or nearly exact. Application of the proposed solutions is demonstrated using a practical example. The proposed solutions, which make the design of grass-lined channels easier and more efficient, should be of interest to the hydraulic engineering community.

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)0.001
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.017
GPT teacher head0.200
Teacher spread0.183 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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Same venueProceedings of the Institution of Civil Engineers - Water ManagementSame topicHydraulic flow and structuresFrench-language works237,207